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., Galvรฃo, 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., Galvรฃo, G., Louro, P., Vรฉstias, M., & Vieira, P. (2024). Enhancing urban intersection efficiency: Utilizing visible light communication and learning-driven control for improved traffic signal performance. Vehicles, 6(2), 666โ€“692.

Galvรฃo, G., Vieira, M., Louro, P., Vieira, M. A., Vรฉstias, 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. 60โ€“65).

Vieira, M., Galvรฃo, 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.

Galvรฃo, G., Vieira, M., Louro, P., Vieira, M. A., Vรฉstias, 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.

Nitin Goyal | Computer Science | Best Researcher Award

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Dr. Nitin Goyal | Computer Science | Best Researcher Award

Assistant Professor | Central University of Haryana | India

Dr. Nitin Goyal is a distinguished academic and researcher in the field of Computer Science and Engineering, recognized for his extensive contributions to advanced computing technologies, underwater wireless sensor networks (UWSN), and intelligent communication systems. With a robust academic foundation and over sixteen years of professional experience, he has established a prolific research profile encompassing artificial intelligence, machine learning, deep learning, Internet of Things (IoT), and wireless sensor networks (WSN). Dr. Nitin Goyal has authored more than 175 research papers, including 90 SCI-indexed, 15 Scopus-indexed, 15 book chapters, and numerous conference proceedings, reflecting his commitment to high-impact scientific dissemination. His innovative work has led to the filing of 30 patents, with 20 already granted, demonstrating his drive for technological advancement and innovation. As an editor and contributor to multiple international books published by CRC Press, IGI Global, and Cambridge Scholars, he plays a vital role in bridging research and industry applications. His active engagement as a reviewer, editorial board member, and guest editor for renowned SCI journals such as Scientific Reports (Nature) and CMC โ€“ Computers, Materials & Continua further emphasizes his scholarly leadership. Dr. Nitin Goyal research excellence has been recognized globally through awards such as the Best Researcher Award and his inclusion in the list of the worldโ€™s top 2% scientists by Elsevier. His recent works on AI-driven pest classification, privacy-preserving frameworks, and intelligent anti-phishing models underscore his continuous pursuit of innovation for sustainable and secure technological ecosystems. 3,747 Citations by 2,904 documents, 128 Documents, 35 h-index.

Profiles: Scopus | Orcid | Google Scholar | Researchgate | LinkedInย 

Featured Publications

Trivedi, N. K., Gautam, V., Anand, A., Aljahdali, H. M., Villar, S. G., Anand, D., … (2021). Early detection and classification of tomato leaf disease using high-performance deep neural network. Sensors, 21(23), 7987.

Kumar, A., Sharma, S., Goyal, N., Singh, A., Cheng, X., & Singh, P. (2021). Secure and energy-efficient smart building architecture with emerging technology IoT. Computer Communications, 176, 207โ€“217.

Lilhore, U. K., Imoize, A. L., Li, C. T., Simaiya, S., Pani, S. K., Goyal, N., Kumar, A., … (2022). Design and implementation of an ML and IoT based adaptive traffic-management system for smart cities. Sensors, 22(8), 2908.

Chaudhary, M., Goyal, N., Benslimane, A., Awasthi, L. K., Alwadain, A., & Singh, A. (2022). Underwater wireless sensor networks: Enabling technologies for node deployment and data collection challenges. IEEE Internet of Things Journal, 1.

Goyal, N., Dave, M., & Verma, A. K. (2020). SAPDA: Secure authentication with protected data aggregation scheme for improving QoS in scalable and survivable UWSNs. Wireless Personal Communications, 113(1), 1โ€“15.

Miodrag Spalevic | Numerical Analysis | Best Researcher Award

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Prof. Dr. Miodrag Spalevic | Numerical Analysis | Best Researcher Award

Professor | University of Belgrade | Serbia

Prof. Dr. Miodrag Spalevic is a distinguished full professor in the Department of Mathematics at the Faculty of Mechanical Engineering, University of Belgrade, with additional teaching at the Mathematical Grammar School in Belgrade. He completed his PhD studies in mathematics at the universities of Kragujevac and Montenegro and serves as an external member of the University of Athens for faculty selection in numerical analysis, approximation theory, and numerical integration. Prof. Dr. Miodrag Spalevic has made significant contributions as editor and referee for numerous international journals and is actively involved in shaping research in applied and numerical analysis, scientific computing, and quadrature theory, particularly focusing on Gaussian-type quadrature formulas and orthogonal polynomials. He has authored over a hundred papers and several influential books and chapters, mentoring numerous MSc and PhD theses. His research explores advanced quadrature rules, error bounds, and numerical algorithms, emphasizing practical computation for analytic functions and Fourier coefficients. Prof. Dr. Miodrag Spalevic has participated in and contributed to a wide array of international conferences, delivering invited lectures, plenary talks, and keynote presentations, while also organizing specialized minisymposia. His work bridges rigorous theoretical development with practical computational methods, making him a leading figure in approximation, quadrature, and scientific computing. He has 88 documents with 723 citations, an h-index of 14, and is widely recognized for his editorial and academic leadership across global mathematical communities.

Profile: Scopus | Orcid | Researchgateย 

Featured Publications

Milovanoviฤ‡, G. V., & Spaleviฤ‡, M. M. (1998). Construction of Chakalovโ€“Popoviciuโ€™s type quadrature formulae. Rend. Circ. Mat. Palermo, 52, 625โ€“636.

Spaleviฤ‡, M. M. (1999). Besselโ€™s inequality in terms of a basis of Vk. Acta Sci. Math. (Szeged), 65, 169โ€“177.

Spaleviฤ‡, M. M. (1999). Product of Turรกn quadratures for cube, simplex, surface of the sphere, Ern, Er2n. Journal of Computational and Applied Mathematics, 106, 99โ€“115.

Spaleviฤ‡, M. M. (2002). Quadrature formulae of Radau and Lobatto type connected to s-orthogonal polynomials. Zh. Vychisl. Mat. Mat. Fiz., 42, 615โ€“626.

Spaleviฤ‡, M. M. (2001). Remainder term in Chakalovโ€“Popoviciu quadratures of Radau and Lobatto type and influence function. Publ. Inst. Math. (Beograd) (N.S.), 70(84), 79โ€“93.

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 ๐Ÿ‡ฎ๐Ÿ‡ณ, 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. ๐Ÿ‘ฉโ€๐Ÿซ๐ŸŒฟ๐Ÿ“Š

Profile

Orcid

Education ๐ŸŽ“

Dr. Ghosh holds a Ph.D. in Engineering (2019โ€“2024) from Jadavpur University, Kolkata, with her thesis focusing on โ€œAlgorithms for Data Mining: Applications in Biodiversityโ€ ๐Ÿง ๐ŸŒฑ. She earned her M.E. in Multimedia Development from the same university (2011โ€“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 Girlsโ€™ High School. ๐ŸŽ“

Experience ๐Ÿ’ผ

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 (2024โ€“Present). Previously, she worked at Narula Institute of Technology (2022โ€“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 (2015โ€“2017) and Bengal College of Engineering and Technology (2013โ€“2015). ๐Ÿ’ป๐Ÿ“š

Research Interest ๐Ÿ”

Dr. Ghoshโ€™s research bridges Data Science and Ecology through Computational Biodiversity ๐ŸŒ๐Ÿงฌ. 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. ๐Ÿ“ˆ๐ŸŒ

Awards ๐Ÿ†

Dr. Ghosh is a UGC NET qualifier (2017 & 2018) and was awarded the prestigious DST Women Scientists Fellowship (2019โ€“2022), where she led a โ‚น22 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. ๐Ÿ…๐ŸŒŸ

Publications ๐Ÿ“„

๐Ÿ“– Ghosh et al. (2023). โ€œAn Irregular CLA-based Novel Frequent Pattern Mining Approach.โ€ International Journal of Data Mining, Modelling and Management. DOI

๐Ÿ“– Ghosh et al. (2022). โ€œRecognition of Coexistence Pattern of Salt Marshes and Mangroves.โ€ Ecological Informatics. DOI

๐Ÿ“– Ghosh et al. (2022). โ€œFrequent itemset mining using FP-tree.โ€ Innovations in Systems and Software Engineering.

๐Ÿ“– Ghosh et al. (2021). โ€œKnowledge Discovery of Sundarban Mangrove Species.โ€ SN Computer Science. DOI

๐Ÿ“– Ghosh et al. (2021). โ€œPrediction of Interaction between SARS-CoV-2 and Human Protein.โ€ Journal of The Institution of Engineers (India): Series B. DOI

๐Ÿ“– Mondal, Ghosh et al. (2022). โ€œSuffix forest for mining tri-clusters from time-series data.โ€ Innovations in Systems and Software Engineering.

๐Ÿ“– Ghosh & Parekh (2013). โ€œFish shape recognition using multiple shape descriptors.โ€ 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 ๐Ÿ‡ฏ๐Ÿ‡ต๐Ÿ‡ฉ๐Ÿ‡ฐ 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. ๐ŸŒ๐Ÿ’ป

Profile

Google Scholar

Education ๐ŸŽ“

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. ๐ŸŽ“๐Ÿ“˜๐ŸŒ

Experience ๐Ÿ’ผ

Dr. Yasuokaโ€™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. ๐Ÿซ๐ŸŒ๐Ÿ‘ฉโ€๐Ÿซ

Research Interest ๐Ÿ”

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. Yasuokaโ€™s work aligns technology with human-centric values and social innovation. ๐Ÿค–๐Ÿ™๏ธ๐Ÿ‘ฅ

Awards ๐Ÿ†

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. ๐Ÿ†๐Ÿ“šโœจ

Publications ๐Ÿ“„

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.
๐Ÿ”— 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.
๐Ÿ”— 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.
๐Ÿ”— 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.