Angeliki Paraskevopoulou | Landscape Architecture | Best Researcher Award Published on 14/11/202514/11/2025 by Environmental Scientists Ms. Angeliki Paraskevopoulou | Landscape Architecture | Best Researcher Award Associated Professor | Agricultural University of Athens | Greece Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Ms. Angeliki Paraskevopoulou is a distinguished researcher in landscape architecture, urban green infrastructure, and ornamental plant science, with extensive experience in academia and professional practice across Greece and the UK. Her work bridges agricultural science, environmental design, and landscape management, focusing on resilient public spaces, historical parks, therapeutic landscapes, and climate-responsive planting strategies. She has contributed significantly to sustainable landscape planning through numerous research projects funded by European, national, and local organizations, addressing themes such as urban heat mitigation, nature-based solutions, agroecology, and ecological restoration. Her research portfolio includes studies on schoolyard greening, healing gardens, post-fire landscape perceptions, visitor needs in historical parks, and the impact of environmental features on human wellbeing, employing innovative tools such as biosensors and perception analysis. Her publication record in reputable international journals showcases her interdisciplinary expertise and her ability to integrate scientific evidence into practical design approaches. With an early career shaped by agronomy and landscape architecture, she developed strong foundations in plant science, horticulture, and community-centered design, complemented by award-winning contributions at major horticultural exhibitions. She continues to enhance academic excellence through teaching, supervising research, and reviewing scientific manuscripts. Paraskevopoulou’s leadership in collaborative initiatives underscores her dedication to advancing inclusive, sustainable, and culturally informed landscape transformations, supporting greener cities and climate-adaptive public spaces, as reflected in her academic footprint with 430 citations by 399 documents, 49 documents, and an h-index of 13. Profiles: Scopus | Orcid | Google Scholar
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Featured Publications Kotsiris, G., Nektarios, P. A., & Paraskevopoulou, A. T. (2012). Lavandula angustifolia growth and physiology is affected by substrate type and depth when grown under Mediterranean semi-intensive green roof conditions. HortScience, 47(2), 311–317. Akoumianaki-Ioannidou, A., Paraskevopoulou, A. T., & Tachou, V. (2016). School grounds as a resource of green space to increase child-plant contact. Urban Forestry & Urban Greening, 20, 375–386. Gkoltsiou, A., & Paraskevopoulou, A. (2021). Landscape character assessment, perception surveys of stakeholders and SWOT analysis: A holistic approach to historical public park management. Journal of Outdoor Recreation and Tourism, 35, 100418. Paraskevopoulou, A. T., & Kamperi, E. (2018). Design of hospital healing gardens linked to pre- or post-occupancy research findings. Frontiers of Architectural Research, 7(3), 395–414. Paraskevopoulou, A. T., Kamperi, E., Demiris, N., Economou, M., Theleritis, C., & others. (2018). The impact of seasonal colour change in planting on patients with psychotic disorders using biosensors. Urban Forestry & Urban Greening, 36, 50–56.
Andsera Adugna Mekonen | Climate Change Mitigation | Women Researcher Award Published on 14/11/202514/11/2025 by Environmental Scientists Mrs. Andsera Adugna Mekonen | Climate Change Mitigation | Women Researcher Award Mrs. Andsera Adugna Mekonen | University of Naples | Italy Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Mrs. Andsera Adugna Mekonen is an emerging researcher in Earth observation, remote sensing, and sustainable agroforestry, recognized for his strong interdisciplinary expertise and innovative scientific contributions. As a PhD student at the University of Naples Federico II, he focuses on integrating drone technologies, satellite imagery, and advanced data science methods to improve biomass estimation and precision agriculture in agroforestry systems. His research advances the use of UAS-based RGB, multispectral, and thermal datasets combined with AI, neural networks, photogrammetry, and supervised learning to monitor vegetation structure and enhance ecosystem productivity. With a foundation in Earth sciences and specialization in remote sensing and geoinformatics, Andsera has developed analytical skills spanning GIS, programming, machine learning, environmental modeling, and geospatial data processing. His earlier work on landslide susceptibility mapping in complex terrains contributed to environmental risk assessment in Ethiopia. He has authored peer-reviewed publications in journals such as Environmental Challenges and Aerospace, and has presented at major international conferences including IEEE MetroAerospace. His achievements have been recognized through the prestigious ENI Award, honoring young African talent in scientific research. Mrs. Andsera Adugna Mekonen training in drone operation, big data foundations for Earth observation, and agricultural remote sensing further strengthens his technical versatility. His collaborations with academic and research institutions reflect a commitment to developing sustainable, data-driven solutions for environmental monitoring and climate-resilient land management. He has 2 citations by 2 documents, 2 documents in total, and holds an h-index of 1, highlighting his early but promising research impact. Through his work, he continues to contribute to the advancement of Earth observation technologies and their application in supporting sustainable agroecosystems and geospatial innovation. Profiles: Scopus | Orcid | Google Scholar
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Featured Publications Mekonnen, A. A., Raghuvanshi, T. K., Suryabhagavan, K. V., & Kassawmar, T. (2022). GIS-based landslide susceptibility zonation and risk assessment in complex landscape: A case of Beshilo watershed, northern Ethiopia. Environmental Challenges, 8, 100586. Cited by: 57 Mekonen, A. A., Accardo, D., & Renga, A. (2024). Above ground biomass estimation in agroforestry environment by UAS and RGB imagery. In 2024 11th International Workshop on Metrology for AeroSpace (MetroAeroSpace). Cited by: 3 Mekonen, A. A., Accardo, D., & Renga, A. (2025). Above-ground biomass prediction in agroforestry areas using machine learning and multispectral drone imagery. In 2025 IEEE 12th International Workshop on Metrology for AeroSpace. Cited by: 1 Mekonen, A. A., Conte, C., & Accardo, D. (2025). An effective process to use drones for above-ground biomass estimation in agroforestry landscapes. Aerospace, 12(11), 1001. Sisay Belete, S. B., Melkamu Bezabih, M. B., Birhan Abdulkadir, B. A., … (2019). Inoculation and phosphorus fertilizer improve food-feed traits of grain legumes in mixed crop-livestock systems of Ethiopia.
Valens Habimana | Wastewater Treatment | Best Researcher Award Published on 14/11/202514/11/2025 by Environmental Scientists Mr. Valens Habimana | Wastewater Treatment | Best Researcher Award KTH university | Sweden Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Mr. Valens Habimana is a dedicated PhD student at KTH University whose research expertise spans environmental chemistry, wastewater treatment, and sustainable resource recovery. With a strong scientific foundation shaped by advanced training in environmental sanitation and years of academic engagement, he has contributed significantly to advancing water quality improvement and environmental monitoring initiatives. His work explores innovative treatment solutions such as microbial systems, natural fibers, adsorption techniques, and constructed wetlands, aiming to enhance pollutant removal while promoting circular resource use through biogas generation, nutrient recovery, and water reuse. He has been involved in impactful studies on heavy metals, pesticide residues, pharmaceuticals, food nutrient retention, and the ecological health of freshwater bodies, and holds a growing scholarly presence with 71 citations by 69 documents, 4 documents indexed, and an h-index of 2. His research has appeared in reputable journals such as Science of the Total Environment, Food Science & Nutrition, Water, and other regional and international scientific outlets. Mr. Valens Habimana has collaborated with renowned institutions and environmental organizations to drive research innovations addressing local and global environmental challenges. His contributions also extend to national programs focused on industrial effluent assessments, water quality monitoring, and green growth best-practice verification. As a committed member of several scientific networks and standards committees, he actively promotes knowledge exchange and scientific leadership. Through his ongoing doctoral research and collaborative projects, Valens continues to advance sustainable water management, environmental protection, and applied analytical chemistry, positioning himself as a rising researcher dedicated to impactful, solution-oriented scientific work. Profile: Scopus
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Featured Publications Habimana, V., & co-authors. (2024). Characterization and treatment of academic wastewater using volcanic-gravel-constructed wetlands: A study in Rwanda. Water, 17(22), 3200. Habimana, V., & co-authors. (2024). Bioaccumulation of trace elements in fish from Lake Kivu and its potential risk to consumers in Rwanda. Habimana, V., & co-authors. (2021). Assessment of heavy metals in water from Lake Kivu, Rwanda. In Recent advances in environmental science from the Euro-Mediterranean and surrounding regions (2nd ed., pp. 655–660). Habimana, V., & co-authors. (2020). Water physico-chemical characteristics of the Lakes Burera and Ruhondo, Rwanda.
Anam Farzand | Molecular Biology | Best Researcher Award Published on 14/11/202514/11/2025 by Environmental Scientists Ms. Anam Farzand | Molecular Biology | Best Researcher Award Sultan Zainal Abidin University | Malaysia Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Ms. Anam Farzand is a dedicated molecular biology researcher and academic whose work spans advanced laboratory sciences, cancer biology, nanotechnology, obesity genetics, and infectious disease studies, with 17 citations by 17 documents, 5 documents published, and an h-index of 2 reflecting her growing scholarly impact. As a PhD scholar, her research interests integrate obesity, nutrition, genetic predisposition, and molecular mechanisms influencing metabolic disorders. She has contributed significantly to scientific literature through publications on genomics-based nutrition, syndromic obesity, food marketing influences, viral oncology, nanostructured lipid carriers, and microbial bioactive compounds. Her earlier research explored anticancer activities of wild olive extract using lipid-based nanoparticles and the biochemical impacts of dengue infection on liver function parameters, reflecting her strong foundation in experimental design and biomedical investigation. She possesses hands-on expertise in molecular techniques including PCR, ELISA, gel electrophoresis, blotting methods, cell culture, nanoparticle formulation, microscopy, and advanced analytical assessments. Her professional journey includes extensive teaching in biophysics, pathology, immunology, biotechnology, hematology, endocrinology, and related biosciences, along with experience supervising numerous undergraduate and graduate research projects. She has also facilitated academic programs in specialized health sciences, contributing to curriculum support, student mentorship, and research coordination. Her scholarly engagement extends to peer reviewing for reputable journals and contributing to scientific conferences, demonstrating her active role in academic development and quality research dissemination. With strong analytical capabilities and a passion for innovative biomedical solutions, she continues to advance research at the interface of molecular biology, clinical sciences, and translational health technologies. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Featured Publications Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., … (2022). Updates on Epstein–Barr Virus (EBV)-associated nasopharyngeal carcinoma: Emphasis on the latent gene products of EBV. Medicina, 59(1), 2. Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., … (2025). The microbial sources of bioactive compounds: Potential anticancer therapeutic options. Nano LIFE, 15(04), 2430007. Iqbal, M., Farzand, A., Ahmad, I., Iqbal, S., & Mubeen, A. (2022). Comparative study of hematological profile variation in three trimesters of pregnancy: Study of hematological profile variation in pregnancy. Pakistan BioMedical Journal, 23–27. Malik, S., Awan, S. J., Farzand, A., & Ali, Q. (2022). Inflammation reduction potential of nanostructured lipid carriers encapsulated with rat’s bone marrow cells’ lysate. Brazilian Journal of Biology, 82, e269553. Farzand, A. (2021). A review on the medicinal potential of Trachyspermum ammi found in Pakistan. Journal of Pharmaceutical Research International, 33(41B).
Goncalo Galvao | Electronics and Computer Engineering | Best Researcher Award Published on 14/11/202514/11/2025 by Environmental Scientists Dr. Goncalo Galvao | Electronics and Computer Engineering | Best Researcher Award International Society For Executive Learning | Portugal Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Dr. Goncalo Galvao is a dedicated PhD student at ISEL whose research spans Electronics and Computer Engineering, Optoelectronics, and Machine Learning, with a strong focus on intelligent mobility systems. His academic trajectory reflects a commitment to innovation, particularly in the integration of Visible Light Communication and deep reinforcement learning to develop adaptive traffic control solutions that enhance vehicular communication, improve traffic flow efficiency, and reduce congestion in emerging smart-city environments. His earlier work explored advanced optical wireless systems for connected vehicles, leading to high-quality scientific contributions and recognition through a Best Paper Award at an international conference. Dr. Goncalo Galvao has authored a substantial body of research indexed in Scopus, comprising 21 documents with 64 citations across 42 citing sources and a 4 h-index, demonstrating the growing impact and visibility of his contributions to optical communication and AI-driven traffic management. His research involvement includes participation in a funded project centered on intelligent transportation and urban mobility challenges, where he applies data-driven engineering approaches to develop sustainable and efficient solutions. His ongoing doctoral research further advances this trajectory, positioning him at the forefront of innovative developments in smart mobility and next-generation transportation systems. Through his scholarly output, project engagements, and academic involvement, Dr. Goncalo Galvao continues to contribute meaningfully to advancements in optical wireless communication, machine learning applications in engineering, and the development of intelligent systems that support safer, smarter, and more efficient urban mobility infrastructures. Profiles: Scopus | Orcid | Google Scholar | Researchgate
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Featured Publications Vieira, M. A., Galvão, G., Vieira, M., Louro, P., Vestias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Visible light communication and learning-based control for traffic signal optimization and vehicle management. Symmetry, 16(2), 240. Vieira, M., Vieira, M. A., Galvão, G., Louro, P., Véstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666–692. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2023). Visible light communication at urban intersections to improve traffic signaling and cooperative trajectories. In 2023 7th International Young Engineers Forum (YEF-ECE) (pp. 60–65). Vieira, M., Galvão, G., Vieira, M. A., Vestias, M., Louro, P., & Vieira, P. (2024). Integrating visible light communication and AI for adaptive traffic management: A focus on reward functions and rerouting coordination. Applied Sciences, 15(1), 116. Galvão, G., Vieira, M., Louro, P., Vieira, M. A., Véstias, M., & Vieira, P. (2024). Multi agent reinforcement learning system for vehicular and pedestrian traffic control with visible light communication. In 2024 8th International Young Engineers Forum on Electrical and Computer Engineering.
Adamantia Pseftogka | Veterinary Medicine | Best Researcher Award Published on 11/11/202511/11/2025 by Environmental Scientists Dr. Adamantia Pseftogka | Veterinary Medicine | Best Researcher Award University of Thessaly | Greece Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Dr. Adamantia Pseftogka is a dedicated veterinary researcher specializing in dermatology at the University of Thessaly. A graduate of the School of Veterinary Medicine at the same university, she has developed strong clinical and research expertise through her work in both first- and second-opinion veterinary practices before commencing her residency at the European College of Veterinary Dermatology (ECVD). Her primary research interests lie in the study of dermatological conditions affecting companion animals, particularly canine skin health and immunological disorders. She has contributed to peer-reviewed publications exploring lymph node cytology in dogs with leishmaniasis and the effects of dermatological treatments on canine skin hydration. Her research emphasizes diagnostic precision, treatment efficacy, and improved veterinary care through evidence-based dermatological protocols. Dr. Pseftogka has participated in collaborative research projects led by distinguished investigators, contributing to advancements in veterinary cytology and dermatopathology. Her professional affiliations include membership in the Hellenic Society of Veterinary Dermatology, the European Society of Veterinary Dermatology (ESVD), and the European College of Veterinary Dermatology (ECVD). Although at an early stage in her academic journey, she has demonstrated commendable scientific potential through her analytical approach, interdisciplinary collaborations, and commitment to improving animal health. With a growing research portfolio and an ongoing ECVD residency, Dr. Pseftogka continues to build her expertise in veterinary dermatology, aiming to advance diagnostic methodologies, refine clinical interventions, and contribute to the global knowledge base in animal skin health and disease management. Profiles: Orcid
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Featured Publications Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., Kouklaki, E., Mylonakis, M. E., & Saridomichelakis, M. N. (2025, November 8). Evaluation of the repeatability and reproducibility of the results of lymph node cytology for Leishmania amastigotes in dogs without leishmaniosis and in dogs with leishmaniosis before, during, and after treatment. Veterinary Sciences. Pseftogka, A., Samuel (Badulescu), E., Chatzis, M. K., & Saridomichelakis, M. N. (2025, September). Effect of a spray containing occlusive agents, humectants and physiological lipids on skin hydration of healthy dogs when applied after bathing with a chlorhexidine 2%/miconazole 2% shampoo. Veterinary Dermatology.
Samsuzzaman | Agricultural Machinery Engineering | Best Researcher Award Published on 11/11/202511/11/2025 by Environmental Scientists Dr. Samsuzzaman | Agricultural Machinery Engineering | Best Researcher Award Chungnam National University | South Korea Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Dr. Samsuzzaman is an emerging researcher in the field of smart and precision agriculture, focusing on the integration of artificial intelligence, sensor fusion, and digital technologies for sustainable crop and livestock production. His research interests span AI-based smart farming, controlled environment agriculture (CEA), vertical farming, remote sensing in agriculture, and digital livestock farming. His scientific contributions include several high-impact publications in international journals such as Agronomy, Horticulturae, Precision Agriculture, and the Journal of Animal Science and Technology, addressing topics like stress detection in seedlings, plant factory automation, and computer vision applications in livestock systems. His work demonstrates innovative use of machine learning, deep learning, and image processing to enhance environmental monitoring and resource efficiency in agricultural systems. With 181 citations, an h-index of 7, and an i10-index of 4, his research continues to gain recognition globally. Recognized with multiple academic honors, including Best Oral and Poster Presentation Awards from leading Korean scientific societies, Dr. Samsuzzaman actively contributes to interdisciplinary research projects funded by the Ministry of Agriculture, Food and Rural Affairs, South Korea. His recent studies on sensor fusion and machine vision for real-time crop stress quantification are pioneering steps toward next-generation precision agriculture technologies. As a member of international professional societies such as ASABE, ISPA, KSAM, and BKS, he is dedicated to advancing smart farming innovations that promote agricultural sustainability, productivity, and climate resilience through the convergence of automation, data analytics, and environmental intelligence. Profiles: Google Scholar | Orcid
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Featured Publications Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229. Reza, M. N., Ali, M. R., Kabir, M. S. N., Karim, M. R., Ahmed, S., Kyoung, H., Kim, G., & Samsuzzaman. (2024). Thermal imaging and computer vision technologies for the enhancement of pig husbandry: A review. Journal of Animal Science and Technology, 66(1), 31. Islam, S., Reza, M. N., Samsuzzaman, S. A., Cho, Y. J., Noh, D. H., Chung, S. O., & others. (2024). Machine vision and artificial intelligence for plant growth stress detection and monitoring: A review. Precision Agriculture, 6(1), 34. Islam, S., Samsuzzaman, Reza, M. N., Lee, K. H., Ahmed, S., Cho, Y. J., Noh, D. H., & others. (2024). Image processing and support vector machine (SVM) for classifying environmental stress symptoms of pepper seedlings grown in a plant factory. Agronomy, 14(9), 2043. Islam, S., Reza, M. N., Ahmed, S., Samsuzzaman, Lee, K. H., Cho, Y. J., Noh, D. H., & others. (2024). Nutrient stress symptom detection in cucumber seedlings using segmented regression and a mask region-based convolutional neural network model. Agriculture, 14(8), 1390.*
Kabir, M. S. N., Reza, M. N., Chowdhury, M., Ali, M., Samsuzzaman, Ali, M. R., & others. (2023). Technological trends and engineering issues on vertical farms: A review. Horticulturae, 9(11), 1229.
Maria Sebastian Lopez | Geographical Education | Women Researcher Award Published on 11/11/202511/11/2025 by Environmental Scientists Prof. Dr. Maria Sebastian Lopez | Geographical Education | Women Researcher Award Senior Lecturer | University of Zaragoza | Spain Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Prof. Dr. María Sebastián López is a distinguished Spanish scholar whose research bridges geography, education, archaeology, and environmental studies. As a leading academic at the Universidad de Zaragoza, her work explores spatial citizenship, sustainable development, and innovative teaching methodologies using geospatial technologies. She has authored more than seventy publications, including influential journal articles and book chapters that integrate feminist cartography, GIS-based climate change education, and heritage landscape analysis. Her interdisciplinary contributions span topics such as prehistoric landscape transformation, environmental governance, and the role of cartography in civic engagement and digital education. With 342 citations from 308 documents, 15 publications, and an h-index of 9, her academic influence extends across multiple research domains. Prof. Dr. María Sebastián López research emphasizes how geography education can foster global understanding, gender equality, and active citizenship in addressing twenty-first-century challenges. She has collaborated on international projects that combine digital mapping, remote sensing, and participatory learning, advancing the pedagogical application of geospatial data in schools and universities. Through her pioneering work in geography education and cultural landscape research, she continues to promote the integration of spatial thinking, sustainability awareness, and historical consciousness in global educational practices. Profiles: Scopus | Google Scholar | Orcid
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
Featured Publications González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132. García-Ruiz, J. M., Tomás-Faci, G., Diarte-Blasco, P., Montes, L., Domingo, R., Sebastián-López, M., & others. (2020). Transhumance and long-term deforestation in the subalpine belt of the central Spanish Pyrenees: An interdisciplinary approach. Catena, 195, 104744. Sebastián-López, M., & de Miguel González, R. (2020). Mobile learning for sustainable development and environmental teacher education. Sustainability, 12(22), 9757. Montes, L., Domingo, R., González-Sampériz, P., Sebastián, M., Aranbarri, J., & others. (2016). Landscape, resources and people during the Mesolithic and Neolithic times in NE Iberia: The Arba de Biel Basin. Quaternary International, 403, 133–150. Alday, A., Domingo, R., Sebastián, M., Soto, A., Aranbarri, J., & others. (2018). The silence of the layers: Archaeological site visibility in the Pleistocene-Holocene transition at the Ebro Basin. Quaternary Science Reviews, 184, 85–106.
González-Sampériz, P., Utrilla, P., Mazo, C., Valero-Garcés, B., Sopena, M. C., Sebastián-López, M., & others. (2009). Patterns of human occupation during the early Holocene in the Central Ebro Basin (NE Spain) in response to the 8.2 ka climatic event. Quaternary Research, 71(2), 121–132.
Wenyuan Zhang | Global Earth Observation | Best Researcher Award Published on 11/11/202511/11/2025 by Environmental Scientists Assoc. Prof. Dr. Wenyuan Zhang | Global Earth Observation | Best Researcher Award Associate Professor | China University of Mining and Technology | China Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Assoc. Prof. Dr. Wenyuan Zhang serves as an Associate Professor and Master’s Supervisor at the School of Environment and Spatial Informatics, China University of Mining and Technology (CUMT). He earned his Ph.D. through the prestigious CUMT–ETH Zurich Joint Program and completed his postdoctoral research at the Xi’an Research Institute of Surveying and Mapping. His research focuses on GNSS remote sensing, multi-scale meteorology, water vapor detection, and climate change applications, emphasizing advanced data fusion and satellite geodesy. Assoc. Prof. Dr. Wenyuan Zhang has authored over 16 peer-reviewed publications, including 10 SCI-indexed papers, six of which appear in top-tier CAS journals such as IEEE Transactions on Geoscience and Remote Sensing, Journal of Geodesy, and GPS Solutions. His innovative work on multi-source resilient fusion techniques has significantly advanced the precision of GNSS water vapor retrieval, providing vital insights into atmospheric processes and climate monitoring. With a total of 210 citations, an h-index of 8, and an i10-index of 7, he has made a notable mark in the field of environmental and geodetic sciences. His achievements include winning the Jiangsu Outstanding Doctoral Dissertation Award and the National Ph.D. Scholarship. Beyond his research, Assoc. Prof. Dr. Wenyuan Zhang actively contributes as a reviewer for leading international journals and serves as a member of the IAG Working Group, promoting interdisciplinary collaboration in geodesy and environmental science. His dedication to advancing GNSS-based climate applications continues to strengthen the integration of geospatial technologies in global climate research. Profiles: Google Scholar | Orcid | Researchgate
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Featured Publications Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Crocetti, L., Schartner, M., Zus, F., Zhang, W., Moeller, G., Navarro, V., See, L., et al. (2024). Global, spatially explicit modelling of zenith wet delay with XGBoost. Journal of Geodesy, 98(4), 23. Zhang, W., Zhang, S., Zheng, N., Ding, N., & Liu, X. (2021). A new integrated method of GNSS and MODIS measurements for tropospheric water vapor tomography. GPS Solutions, 25(2), 79. Zhang, W., Zhang, S., Ding, N., Holden, L., Wang, X., & Zheng, N. (2021). GNSS-RS tomography: Retrieval of tropospheric water vapor fields using GNSS and RS observations. IEEE Transactions on Geoscience and Remote Sensing, 60, 1–13. Zhang, W., Zhang, S., Ding, N., & Zhao, Q. (2020). A tropospheric tomography method with a novel height factor model including two parts: Isotropic and anisotropic height factors. Remote Sensing, 12(11), 1848. Liu, X., Zhang, S., Zhang, Q., Zheng, N., Zhang, W., & Ding, N. (2021). Theoretical analysis of the multi-GNSS contribution to partial ambiguity estimation and R-ratio test-based ambiguity validation. GPS Solutions, 25(2), 52.
Fatemeh Avazpour | Hydrology | Best Researcher Award Published on 10/11/202510/11/2025 by Environmental Scientists Dr. Fatemeh Avazpour | Hydrology | Best Researcher Award Yazd University | Iran Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Dr. Fatemeh Avazpour is a dedicated researcher and water-civil engineer specializing in hydrology, hydraulic structures, and water resource management. Her research integrates machine learning, deep learning, and numerical modeling to address complex challenges in river flow, sediment transport, and the impacts of climate change on hydrological systems. She has developed hybrid models combining traditional hydrological approaches with artificial intelligence to improve the accuracy of streamflow and sediment load predictions. Her academic and research journey demonstrates strong analytical expertise, with a focus on GIS and remote sensing applications for watershed management. Dr. Fatemeh Avazpour has contributed to numerous peer-reviewed publications on climate impact assessments, runoff simulation, and sediment prediction, and co-authored technical books on fluid flow and sediment modeling. Recognized for her academic excellence, she has received several awards, including the Best Faculty Award and Top Researcher Recognition. Her international research experience at the University of Oulu, Finland, further strengthened her expertise in advanced hydrological modeling and data-driven water management. She has earned 20 citations by 20 documents, published 4 research papers, and holds an h-index of 2. Dr. Fatemeh Avazpour remains committed to advancing sustainable solutions in the fields of hydraulic engineering, environmental systems, and artificial intelligence applications in hydrology, while actively contributing to professional associations in water and watershed management. Profiles: Scopus
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Featured Publications Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.
Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, June). Flow discharge and suspended sediment load prediction in multiple sites of a basin: A comparative study of classical AI and deep learning approaches. Journal of Acta Geophysica. Avazpour, F., Hadian, M., Talebi, A., & Torabi Haghighi, A. (2025, April). Impact of climate change on river flow using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin. Results in Engineering Journal. Parsaie, A., Avazpour, F., & Afaridegan, E. (2025, March). Numerical modeling of optimal location of drainage and cutoff wall under small concrete dams. Applied Water Science. Avazpour, F., Hadian, M., & Talebi, A. (2025, September). Performance evaluation of the conceptual IHACRES model in simulating runoff in data-scarce semi-arid watersheds. The Journal of Iranian Water Research. Avazpour, F., Hadian, M., & Talebi, A. (2024, June). Evaluation of the performance of machine learning models and optimization algorithms in predicting flow discharge of Kashkan River. Watershed Management Research Journal.