Lamia Fourati | Computer Science | Best Researcher Award

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Prof Dr. Lamia fourati | Computer Science | Best Researcher Award

Computer science and multimedia higher institute of Sfax | Tunisia

Prof. Lamia Chaari Fourati is a distinguished Professor of Telecommunications at the Higher Institute of Computer Science and Multimedia (ISIMS), Sfax University, Tunisia, and a senior researcher at the Digital Research Center of Sfax (CRNS) within the SM@RTS Laboratory. With over two decades of academic and research excellence, she has established herself as one of North Africa’s leading figures in wireless communications, intelligent network systems, and AI-driven communication technologies. Her research is centered on the design, optimization, and security of wireless networks—including Wireless Body Area Networks (WBANs), Internet of Things (IoT), UAV-based networks (FANETs), and Internet of Vehicles (IoV). She has significantly contributed to developing MAC and routing protocols, trust management frameworks, and privacy-preserving communication systems for next-generation wireless infrastructures. Her innovative work also spans AI, machine learning, reinforcement learning, blockchain, and federated learning, applied to 6G, edge, and cloud computing ecosystems, with a focus on security, reliability, and energy efficiency. Prof. Fourati’s international collaborations are extensive. She serves as a Working Group Member in European COST Actions such as INTERACT (CA20120) and CA22168 on Physical Layer Security for Trustworthy and Resilient 6G Systems. She has led and participated in multiple sponsored projects on AI-based secure frameworks for UAVs, trust management in IoV, and smart water systems, in partnership with institutions like University of Troyes (France) and University of Aveiro (Portugal). Her research has also been pivotal in developing autonomous and energy-efficient communication systems for smart cities, vehicular networks, and healthcare applications. A dedicated educator and mentor, Prof. Fourati has supervised numerous Master’s and Ph.D. theses and has served on national and international doctoral juries. Her global academic engagements include visiting professorships in India, delivering advanced courses on LLMs, generative AI, network security, IoT, and mobile networks, as well as invited tutorials and talks at major IEEE and international events such as NoF, CRiSIS, IEEE ICBC, and ICHI. Her distinguished contributions have earned her prestigious recognitions, including the African Union Kwame Nkrumah Regional Scientific Award (2016), Miss.Africa Seed Fund Award (2018), Burj Kallel Award for Best Researcher (2019), and Outstanding Woman in Tech – North Africa (2021). In 2024, she was named among the Top Tunisian Women in Tech. An IEEE Senior Member and active participant in organizations such as OWSD, N2Women, ISOC, and ITU, Prof. Fourati continues to inspire the next generation of researchers and women in STEM. Her work integrates sustainable development, green computing, and ethical AI, aiming to build a future where intelligent, secure, and inclusive communication systems empower societies globally.

Profiles: Scopus | Orcid

Featured Publications

Fourati, L. C. (2024). Investigation of security threat datasets for intra- and inter-vehicular environments. Sensors, 24(11), 3431. https://doi.org/10.3390/s24113431

Fourati, L. C. (2022). Analysis of LoRaWAN 1.0 and 1.1 protocols security mechanisms. Sensors, 22(10), 3717. https://doi.org/10.3390/s22103717

Fourati, L. C. (2022). A genetic algorithm-based intelligent solution for water pipeline monitoring system in a transient state. Concurrency and Computation: Practice and Experience, 34(21), e5959. https://doi.org/10.1002/cpe.5959

Fourati, L. C. (2022). Cyber-physical systems for structural health monitoring: Sensing technologies and intelligent computing. Journal of Supercomputing, 78, 15126–15153. https://doi.org/10.1007/s11227-021-03875-5

Fourati, L. C. (2022). Investigation on vulnerabilities, threats and attacks prohibiting UAVs charging and depleting UAVs batteries: Assessments and countermeasures. Ad Hoc Networks, 131, 102805. https://doi.org/10.1016/j.adhoc.2022.102805

Fourati, L. C. (2021). 5G network slicing: Fundamental concepts, architectures, algorithmics, projects practices, and open issues. Concurrency and Computation: Practice and Experience, 33(24), e6352. https://doi.org/10.1002/cpe.6352

Fourati, L. C. (2021). A convoy of ground mobile vehicles protection using cooperative UAVs-based system. In 2021 International Symposium on Networks, Computers and Communications (ISNCC) (pp. 1–6). IEEE. https://doi.org/10.1109/ISNCC52172.2021.9615724

Fourati, L. C. (2021). A survey of 5G network systems: Challenges and machine learning approaches. International Journal of Machine Learning and Cybernetics, 12, 1–27. https://doi.org/10.1007/s13042-020-01178-4

Fourati, L. C. (2021). Blockchain-based trust management approach for IoV. In Lecture Notes in Networks and Systems (Vol. 206, pp. 455–467). Springer. https://doi.org/10.1007/978-3-030-75100-5_42

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.

 

Shaowei Wang | Computer Science | Distinguished Scientist Award

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Mr. Shaowei Wang | Computer Science | Distinguished Scientist Award

Guangzhou University | China

Dr. Shaowei Wang is currently an Associate Professor at the School of Artificial Intelligence, Guangzhou University. He earned his Ph.D. from the University of Science and Technology of China (USTC) in 2019. Prior to his academic appointment, he worked as an Applied Researcher at Tencent Technology (Shenzhen), where he contributed to industry-grade privacy-preserving solutions. His research primarily focuses on privacy-preserving computing, federated learning, and AI security, with a strong emphasis on differential privacy techniques and secure data sharing protocols. Dr. Wang has an impressive scholarly record, having authored or co-authored over 40 peer-reviewed papers, with 15 publications as the first or corresponding author in top-tier venues such as USENIX Security, IEEE S&P, INFOCOM, and ICDE. As of September 2025, his work has garnered 1,106 citations, achieving an h-index of 16 (Google Scholar indexed), reflecting the impact and relevance of his contributions to the field. He has been the Principal Investigator (PI) for six research projects, including three funded by the National Natural Science Foundation of China, and a key researcher in five national-level and regional-level projects. Notable ongoing research includes work on shuffled differential privacy, privacy attacks on pre-trained models, and secure digital identity protocols. His academic excellence and innovation have earned him multiple accolades, including an Honorable Mention Award at USENIX Security, a Top 3% Paper Award at ICASSP, and the First Prize in Natural Sciences from the Guangdong Artificial Intelligence Association. Dr. Wang remains committed to advancing the frontiers of privacy-preserving AI through impactful research, interdisciplinary collaboration, and high-quality publications in the global research community.

Profile: Scopus | Google Scholar

Featured Publications

Wang, S., Huang, L., Nie, Y., Zhang, X., Wang, P., Xu, H., & Yang, W. (2019). Local differential private data aggregation for discrete distribution estimation. IEEE Transactions on Parallel and Distributed Systems, 30(9), 2046–2059.

Xin, B., Yang, W., Geng, Y., Chen, S., Wang, S., & Huang, L. (2020). Private FL-GAN: Differential privacy synthetic data generation based on federated learning. In ICASSP 2020 – 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. [pages not provided]). IEEE.

Shen, Y., Huang, L., Li, L., Lu, X., Wang, S., & Yang, W. (2015). Towards preserving worker location privacy in spatial crowdsourcing. In 2015 IEEE Global Communications Conference (GLOBECOM) (pp. 1–6). IEEE.

Nie, Y., Yang, W., Huang, L., Xie, X., Zhao, Z., & Wang, S. (2018). A utility-optimized framework for personalized private histogram estimation. IEEE Transactions on Knowledge and Data Engineering, 31(4), 655–669.

Wang, S., Huang, L., Nie, Y., Wang, P., Xu, H., & Yang, W. (2018). PrivSet: Set-valued data analyses with local differential privacy. In IEEE INFOCOM 2018 – IEEE Conference on Computer Communications (pp. 1088–1096). IEEE.

Yang, G., Wang, S., & Wang, H. (2021). Federated learning with personalized local differential privacy. In 2021 IEEE 6th International Conference on Computer and Communication Systems (ICCCS) (pp. [pages not provided]). IEEE.

Xin, B., Geng, Y., Hu, T., Chen, S., Yang, W., Wang, S., & Huang, L. (2022). Federated synthetic data generation with differential privacy. Neurocomputing, 468, 1–10.