Goncalo Galvao | Electronics and Computer Engineering | Best Researcher Award

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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.

Moumita Ghosh | Computer Science | Best Researcher Award

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Dr. Moumita Ghosh | Computer Science | Best Researcher Award

Assistant Professor, Heritage Institute of Technology, India

Dr. Moumita Ghosh (PhD, Engg.) is a passionate researcher from Kolkata, India 🇮🇳, currently working as an Assistant Professor in the Department of Computer Science and Engineering at the Heritage Institute of Technology. Her core research interests lie at the intersection of Data Science and Computational Biodiversity. With a deep commitment to innovation and academia, she integrates machine learning and data mining techniques to address biodiversity conservation and complex ecological data analysis. 👩‍🏫🌿📊

Profile

Orcid

Education 🎓

Dr. Ghosh holds a Ph.D. in Engineering (2019–2024) from Jadavpur University, Kolkata, with her thesis focusing on “Algorithms for Data Mining: Applications in Biodiversity” 🧠🌱. She earned her M.E. in Multimedia Development from the same university (2011–2013) and completed her B.Tech. in Info Technology from WBUT in 2011. She also achieved outstanding academic performance in both her higher secondary and secondary education at Ichapur Girls’ High School. 🎓

Experience 💼

With over a decade of academic experience, Dr. Ghosh has served in key teaching roles at several premier institutions. She currently teaches Data Structures at Heritage Institute of Technology (2024–Present). Previously, she worked at Narula Institute of Technology (2022–2024), Jadavpur University (as a guest faculty and later PI for a DST-funded project), and held Assistant Professor roles at Institute of Engineering and Management (2015–2017) and Bengal College of Engineering and Technology (2013–2015). 💻📚

Research Interest 🔍

Dr. Ghosh’s research bridges Data Science and Ecology through Computational Biodiversity 🌍🧬. Her work includes pattern mining, remote sensing data, complex networks, and biodiversity modeling using advanced machine learning algorithms. She explores how AI and statistical methods can help mitigate biodiversity loss, emphasizing ecological data interpretation and predictive modeling. Her interests extend to deep learning, natural language processing, and ecological network analysis. 📈🌐

Awards 🏆

Dr. Ghosh is a UGC NET qualifier (2017 & 2018) and was awarded the prestigious DST Women Scientists Fellowship (2019–2022), where she led a ₹22 lakh project on biodiversity data mining. She collaborates internationally with Universitas Islam Indonesia and has served as a reviewer and TPC member for various global conferences. She is a proud member of the Computer Society of India (CSI) since 2021. 🏅🌟

Publications 📄

📖 Ghosh et al. (2023). “An Irregular CLA-based Novel Frequent Pattern Mining Approach.” International Journal of Data Mining, Modelling and Management. DOI

📖 Ghosh et al. (2022). “Recognition of Coexistence Pattern of Salt Marshes and Mangroves.” Ecological Informatics. DOI

📖 Ghosh et al. (2022). “Frequent itemset mining using FP-tree.” Innovations in Systems and Software Engineering.

📖 Ghosh et al. (2021). “Knowledge Discovery of Sundarban Mangrove Species.” SN Computer Science. DOI

📖 Ghosh et al. (2021). “Prediction of Interaction between SARS-CoV-2 and Human Protein.” Journal of The Institution of Engineers (India): Series B. DOI

📖 Mondal, Ghosh et al. (2022). “Suffix forest for mining tri-clusters from time-series data.” Innovations in Systems and Software Engineering.

📖 Ghosh & Parekh (2013). “Fish shape recognition using multiple shape descriptors.” International Journal of Computer Applications.

Conclusion

Dr. Moumita Ghosh is a highly suitable candidate for the Best Researcher Award. Her innovative integration of machine learning and biodiversity studies, coupled with a solid record of publications, a granted patent, and a DST fellowship, reflects both depth and societal relevance in her research. With continued international exposure and independent research leadership, she is poised to make significant contributions to science and sustainability.

Mika Yasuoka | Computer | Best Researcher Award

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Dr. Mika Yasuoka | Computer | Best Researcher Award

Associate Professor, Roskilde University, Denmark

Dr. Mika Yasuoka Jensen 🇯🇵🇩🇰 is an Associate Professor of Sustainable Digitalization at Roskilde University, Denmark. With a multicultural background and deep expertise in computer science, informatics, and interaction design, she bridges Japanese, American, and Danish academic traditions. Passionate about co-creation, digital welfare, and Living Labs, Dr. Yasuoka leads global collaborations with universities, public institutions, and tech corporations to shape sustainable digital futures. Her leadership in participatory design, social innovation, and smart city initiatives has made her a prominent voice in advancing technology for societal benefit. 🌍💻

Profile

Google Scholar

Education 🎓

Dr. Yasuoka’s academic journey is a blend of prestigious institutions across three continents. She earned her Ph.D. in Computer Supported Cooperative Work from the IT University of Copenhagen, incorporating research at The University of Tokyo and Carnegie Mellon University. Prior to this, she completed an M.Sc. in Informatics from Kyoto University and a B.Sc. in Library and Information Science from Keio University. Her academic enrichment also includes an exchange program and visiting researcher positions at Carnegie Mellon University in the U.S. 🎓📘🌐

Experience 💼

Dr. Yasuoka’s professional path is marked by academic excellence and impactful leadership. Since 2020, she has been serving as Associate Professor at Roskilde University. She has held roles at institutions including the IT University of Copenhagen, Keio University, and Technical University of Denmark. She has led numerous cross-sectoral projects, blending stakeholder engagement and digital design across borders. Her strategic advisory roles include working with municipalities and government digital agencies in Japan. 🏫🌏👩‍🏫

Research Interest 🔍

Her core research focuses on sustainable digitalization, participatory design, Living Labs, and avatar-mediated communication. She investigates how digital technologies can be co-designed and responsibly integrated into societies to enhance well-being. With a special interest in smart cities, welfare technologies, and design frameworks, Dr. Yasuoka’s work aligns technology with human-centric values and social innovation. 🤖🏙️👥

Awards 🏆

Dr. Yasuoka has received multiple accolades for her innovative contributions. These include the 11th Nextcom Paper Award (2022) for advancing e-government strategy, the 12th KDDI Foundation Book Publishing Grant (2022), and a Best Paper Finalist at IEEE ARSO 2021. She also earned the Human Interface Society Award (2021) for her analysis of stakeholder involvement in welfare technology assessment. 🏆📚✨

Publications 📄

Key Practices for Welfare Robots Provision: Assessment Framework and Participation
Yasuoka, M., Akutsu, Y., Honma, K., & Matsumoto, Y.
IEEE International Conference on Advanced Robotics and Its Social Impacts (ARSO), 2021.
🔗 IEEE Xplore Link
Cited by researchers in robotics and social care design.

How Remote-Controlled Avatars Are Accepted in Hybrid Workplace
Yasuoka, M., Miyata, T., Nakatani, M., Taoka, Y., & Hamaguchi, N.
In: Distributed, Ambient and Pervasive Interactions, Lecture Notes in Computer Science, vol. 14036, Springer, Cham, 2023.
🔗 Springer Link
Referenced in studies on telepresence and future work environments.

Not Just Power: Exploring Transitions as Fluidity and Relationality in Participatory Design
Yasuoka, M., & Kibi, Y.
Participatory Design Conference 2024, Vol. 2: Exploratory Papers and Workshops.
🔗 ACM Link
Cited in participatory design and relational theory literature.

Reflection on Digital Cities
Yasuoka, M., & Ishida, T.
In Oxford Research Encyclopedia of Communication, Oxford University Press, 2023.
Used in urban digital studies and smart city curricula.

Conclusion

Dr. Mika Yasuoka Jensen is highly suitable for the Best Researcher Award. Her cross-cultural expertise, commitment to societal impact through digitalization, leadership in international projects, and award-winning research achievements make her a standout candidate. Minor enhancements in research metrics and journal profile would further strengthen her already impressive credentials.

Fernando Bruno Dovichi Filho | Engineering | Best Researcher Award

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Prof. Fernando Bruno Dovichi Filho | Engineering | Best Researcher Award

Professor, UNIFEI/UFSCAR, Brazil

Fernando Bruno Dovichi Filho 🇧🇷 is a Brazilian Mechanical Engineer with a Ph.D. in Mechanical Engineering, specializing in energy systems, renewable energy, and thermal modeling. With a rich blend of academic and research experience, he is currently a Substitute Professor at the Federal Institute of São Paulo (IFSP – Piracicaba campus). His work focuses on computational modeling, biomass energy, and sustainability-driven technologies, actively contributing to Brazil’s bioenergy development. Fernando’s background includes hands-on research in high-precision machining, hybrid propulsion, and energy conversion systems.

Profile

Orcid

Education 🎓

Fernando completed his Ph.D. in Mechanical Engineering (2017–2022) at the Federal University of Itajubá (UNIFEI), where he analyzed the technical and economic potential of electricity generation from biomass in Minas Gerais 🌱⚡. He earned his Master’s degree (2013–2015) at the same institution, refining thermal property estimation methods. His Bachelor’s in Industrial Mechanical Engineering (2008–2012) from ETEP Faculdades included a project on optical glass machining 🔧📐, showcasing his early inclination toward precision engineering and energy systems.

Experience 💼

With teaching and research roles across premier institutions, Fernando’s career spans from academia to aerospace research. Currently a full-time Substitute Professor at IFSP – Piracicaba (2023–present), he develops curricula, teaches engineering courses, and guides research and extension projects 🧑‍🏫📊. He previously served as a Substitute Professor at IFMS in 2016. As a PBIC/CNPq Research Fellow, he contributed to advanced propulsion research at both IAE and IEAv from 2009 to 2012, specializing in hybrid rocket engines, high-voltage discharges, and detonation studies using NASA CEA software 🚀💻.

Research Interest 🔍

Fernando’s research integrates renewable energy, thermal systems, and decision-making methodologies. His main focus is on biomass-based electricity generation, thermophysical property modeling, and multi-criteria decision analysis (MCDA) with GIS integration 🌍🧪. He is also keen on advancing thermal estimation techniques, applying hybrid modeling tools like MATLAB and EES, and evaluating the technology readiness of green energy solutions in Brazil and globally.

Awards 🏆

Fernando’s research integrates renewable energy, thermal systems, and decision-making methodologies. His main focus is on biomass-based electricity generation, thermophysical property modeling, and multi-criteria decision analysis (MCDA) with GIS integration 🌍🧪. He is also keen on advancing thermal estimation techniques, applying hybrid modeling tools like MATLAB and EES, and evaluating the technology readiness of green energy solutions in Brazil and globally.

Publications 📄

📖 Evaluation of TRL for biomass electricity technologies, Journal of Cleaner Production, 2021
DOI Link – Cited in renewable energy feasibility studies worldwide.

📖 GIS-MCDM methodology for biomass selection, Agriculture, 2025
DOI Link – A key reference for geo-spatial biomass planning.

📖 An approach to technology selection, Energy, 2023
DOI Link – Cited in works addressing clean technology prioritization.

📘 Book Chapter: From Crops and Wastes to Bioenergy, Woodhead Publishing, 2025

Publisher Link – Cited by authors in sustainable agriculture and energy.

Conclusion

Based on his research achievements, publications, and experience, Fernando Bruno Dovichi Filho is a suitable candidate for the Best Researcher Award. His contributions to sustainable energy solutions and his expertise in thermal systems optimization and renewable energy systems demonstrate his potential to make a significant impact in the field. With some further emphasis on international collaborations and publishing in top-tier journals, he is well-positioned to continue making meaningful contributions to research.