Chao Wang | Computer Science and Artificial Intelligence | Research Excellence Award

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Mr. Chao Wang | Computer Science and Artificial Intelligence | Research Excellence Award

North China University of Technology | China

Dr. Chao Wang, an accomplished Associate Professor at the North China University of Technology, is a distinguished researcher whose work significantly advances the fields of vehicular networks, IoT security, and edge computing. Holding a Ph.D. in Computer Science, Dr. Wang has developed a strong academic portfolio grounded in deep technical expertise and innovative thinking. His research addresses some of the most pressing challenges in intelligent transportation systems, focusing on secure data communication, privacy-preserving mechanisms, and efficient resource allocation in highly dynamic vehicular environments. With 23 publications in SCI and Scopus-indexed journals and conferences, his work demonstrates a consistent trajectory of high-quality scientific output. His research impact is further reflected in 660 citations, an H-index of 10, and an i10-index of 10, according to Google Scholar as of December 3, 2025. These metrics underscore his growing global influence and the relevance of his contributions to next-generation intelligent mobility systems. Dr. Wang has successfully completed and continues to lead multiple national and provincial research projects, focusing on enhancing the reliability, safety, and intelligence of connected vehicle ecosystems. His innovations include blockchain-based frameworks for secure traffic data management, anomaly detection systems for vehicle-to-vehicle communication, and privacy-preserving architectures for IoT-enabled transportation infrastructures. With four patents published or under process, he demonstrates strong translational capability, often transforming theoretical models into practical, real-world solutions. His collaborations with researchers from Springer Nature, IEEE, and various international universities highlight his interdisciplinary approach and commitment to advancing global research partnerships. Although he has not yet undertaken industry consultancy projects, Dr. Wang’s research outputs inherently serve industrial needs, especially in smart transportation, urban planning, and secure IoT deployment. He is also an active professional member of IEEE, contributing to the broader scientific community through peer review, academic exchanges, and participation in scholarly networks. Beyond research, Dr. Wang is dedicated to academic mentorship, guiding students who have achieved recognition in national-level competitions, illustrating his commitment to nurturing the next generation of innovators. With strong expertise, a solid publication record, impactful innovations, and a dedication to advancing secure and intelligent transportation systems, Dr. Wang exemplifies the qualities celebrated by the Research Excellence Award. His achievements reflect not only academic rigor but also societal relevance, making him a highly deserving nominee for this international honor.

Profile: Orcid

Featured Publications

Li, J., Wang, C., Seo, D., Cheng, X., He, Y., Sun, L., Xiao, K., & Huo, Y. (2021). Deep learning-based service scheduling mechanism for GreenRSUs in the IoVs. Wireless Communications and Mobile Computing, 2021, Article 7018486. https://doi.org/10.1155/2021/7018486

Wang, C. (2020). Destination prediction-based scheduling algorithms for message delivery in IoVs. IEEE Access, 8, 1–15. https://doi.org/10.1109/ACCESS.2020.2966494

Wang, C. (2018). A blockchain-based privacy-preserving incentive mechanism in crowdsensing applications. IEEE Access, 6, 1–12. https://doi.org/10.1109/ACCESS.2018.2805837

Wang, C. (2015). A reliable broadcast protocol in vehicular ad hoc networks. International Journal of Distributed Sensor Networks, 11(8), Article 286241. https://doi.org/10.1155/2015/286241

Wang, C. (2015). Ads dissemination in vehicular ad hoc networks. In 2015 IEEE International Conference on Communications (ICC) (pp. 1–6). IEEE. https://doi.org/10.1109/ICC.2015.7248890

Wang, C. (2014). Schedule algorithms for file transmission in vehicular ad hoc networks. In Wireless Algorithms, Systems, and Applications (pp. 135–147). Springer. https://doi.org/10.1007/978-3-319-07782-6_12

Wang, C. (2014). S-disjunct code-based MAC protocol for reliable broadcast in vehicular ad hoc networks. In 2014 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI) (pp. 1–6). IEEE. https://doi.org/10.1109/IIKI.2014.66

Ramkumar Kalyanaraman | Computer Science | Outstanding Scientist Award

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Prof. Dr. Ramkumar Kalyanaraman | Computer Science | Outstanding Scientist Award

Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology | India

Dr. K. Ramkumar is a distinguished academician, researcher, and innovator with over twenty-three years of rich teaching and research experience in the field of Engineering and Computer Science. He is presently serving as a Professor in the Department of Computer Science and Engineering at Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai, Tamil Nadu, India. His illustrious academic journey is marked by consistent dedication to research, innovation, and academic excellence. He obtained his Doctor of Philosophy (Ph.D.) in Computer Science and Engineering from Manonmaniam Sundaranar University, Tirunelveli, in 2018, specializing in Security and Privacy in Cloud Computing, a domain of critical importance in the digital era. To further enhance his expertise and broaden his research perspectives, he pursued a Post-Doctoral Fellowship (PDF) at the Federal University of Ceará, Fortaleza, Brazil, in 2023, focusing on Artificial Intelligence and Biomedical Data Analytics. Throughout his career, Dr. Ramkumar has held several prestigious leadership positions in academia, contributing extensively to institutional growth and quality enhancement. He has served as Professor and Head of the Department (CSE) at Rajalakshmi Institute of Technology, Chennai, and earlier as Professor and Associate Dean (Engineering & Technology) at SRM University, Delhi-NCR, Sonepat, Haryana, where he also chaired the Board of Studies. His earlier academic affiliations include SRM Institute of Science and Technology (Vadapalani Campus, Chennai), Kings Engineering College, and Indira Institute of Engineering and Technology, where he also functioned as Director of Placements. His industry exposure includes working with global technology companies such as Satyam Computer Services Ltd. and LogicaCMG Pvt. Ltd. (now CGI), where he held roles as Associate Consultant, IT Consultant, and Project Leader, leading large technical teams across onshore and offshore environments. Dr. Ramkumar’s research interests encompass a broad spectrum of emerging technologies including Cloud Computing Security, Artificial Intelligence, Machine Learning, IoT Frameworks, Blockchain Systems, and Biomedical Data Analytics. His prolific research output includes numerous publications in SCI, Scopus, and Web of Science-indexed journals, with several articles published in reputed platforms such as Elsevier, Springer, Taylor & Francis, and IEEE. His recent works focus on AI-based diabetic risk prediction, intelligent human activity recognition for assistive technologies, quantum image encryption, and deep learning applications for medical imaging. According to his Google Scholar profile, Dr. Ramkumar has achieved over 1,327 citations, with an h-index of 18 and an i10-index of 24, reflecting the global impact and scholarly recognition of his research contributions. His academic influence extends beyond publications, as he has co-supervised several Post-Doctoral Fellows at the Singapore Institute of Technology, demonstrating his commitment to mentoring and nurturing emerging researchers. Dr. Ramkumar has also published and been granted multiple patents across domains such as wireless sensor networks, mobile ad hoc networks, IoT-based monitoring systems, AI-driven diagnostic tools, and environmental pollution control mechanisms, reflecting his strong inclination toward innovation-driven applied research. Dr. K. Ramkumar stands as a dynamic academic leader whose contributions bridge academia, research, and industry, exemplifying excellence in technological innovation, knowledge dissemination, and professional leadership. His remarkable blend of teaching expertise, research achievements, and administrative acumen continues to inspire students, scholars, and peers across the global academic and scientific community.

Profiles: Scopus | Google Scholar

Featured Publications

Ramkumar, K. (2022). A comparative analysis of methods of endmember selection for use in subpixel classification: A convex hull approach. Computational Intelligence and Neuroscience, 2022, Article ID 3770871

Ramkumar, K., Ananthi, N., Brabin, D. R. D., Goswami, P., Baskar, M., & Bhatia, K. K. (2021). Efficient routing mechanism for neighbour selection using fuzzy logic in wireless sensor network. Computers & Electrical Engineering, 94, 107365.

Banerjee, U., Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to dimension eight: Integrating out heavy scalar(s). The European Physical Journal Plus, 139(2), 1–29.

Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to dimension eight: Integrating out heavy fermion(s). Nuclear Physics B, 1000, 116488.

Ramkumar, K., Medeiros, E. P., Dong, A., de Albuquerque, V. H. C., Hassan, M. R., & Hassan, M. M. (2024). A novel deep learning framework based Swin transformer for dermal cancer cell classification. Engineering Applications of Artificial Intelligence, 133, 108097.

Banerjee, U., Chakrabortty, J., Rahaman, S. U., & Ramkumar, K. (2024). One-loop effective action up to any mass-dimension for non-degenerate scalars and fermions including light–heavy mixing. The European Physical Journal Plus, 139(2), 169.