Dr. Uma Jothi | Team Building and Team Management | Excellence in Research

Amrita University, India

Dr. J. Uma is an accomplished academic and researcher in the fields of information technology, cloud computing, artificial intelligence, and cybersecurity. She holds a B.Tech in Information Technology, an M.E. in Computer Science and Engineering with distinction, and has submitted her Ph.D. thesis in Information and Communication Engineering at Anna University. With more than twelve years of academic experience, she has served as Assistant Professor in leading engineering institutions, contributing significantly to teaching, curriculum development, and research mentorship. Her research focuses on cloud resource allocation, deep reinforcement learning, intelligent optimization algorithms, blockchain technologies, IoT-based systems, and data security. She has published impactful journal articles in reputed outlets like Transactions on Emerging Telecommunications Technologies and Springer’s Lecture Notes in Networks and Systems, along with several book chapters and conference papers. Her work includes innovations in heuristic optimization, adversarial defenses in deep learning, and smart healthcare IoMT solutions. She is also a published patent holder in IoT-based agriculture monitoring systems and employee training platforms. Dr. Uma has organized major AICTE- and RGNIYD-funded programs, contributing to national-level capacity building in data science, IoT, and smart city technologies. Her career reflects a strong commitment to advancing research, innovation, and academic excellence.

Profiles: ORCID

Featured Publications

Arunasree, P. V., Jothi, U., & Sumathi, S. (2025). GA-PoW: A novel genetic algorithm-based proof of work approach for optimal nonce selection in blockchain network. International Journal of Information Technology. https://doi.org/10.1007/s41870-025-02920-3

Yejnakshari, M. K., Bhargav, Y. S., Radhika, N., Jothi, U., Radhika, G., & Mahaveerakannan, R. (2025). Chimp optimization algorithm-based recurrent neural network for smart health care system in edge computing-based IoMT. Journal of Machine and Computing. https://doi.org/10.53759/7669/jmc202505034

Uma, J., Vivekanandan, P., & Shankar, S. (2022). Optimized intellectual resource scheduling using deep reinforcement Q-learning in cloud computing. Transactions on Emerging Telecommunications Technologies, 33(5), e4463. https://doi.org/10.1002/ett.4463

Assoc. Prof. Dr. Ankit Chaudhary | Strategic Leadership | Best Researcher Award

Jawaharlal Nehru University | India

Dr. Ankit Chaudhary is an accomplished Associate Professor in the Cybernetics Group at the School of Engineering, Jawaharlal Nehru University, New Delhi. He earned his Ph.D. in Computer Science and has over 15 years of academic and research experience in artificial intelligence, cyber-physical systems, computer vision, and cybersecurity. Prior to joining JNU, he served as an Assistant Professor at the University of Missouri System, USA, and as a researcher at CSIR-CEERI, India. His scholarly output includes over 105 publications in reputed journals and conferences, four books, and more than 2,950 citations on Google Scholar. Dr. Chaudhary has held visiting positions at prestigious institutions such as the University of Houston–Clear Lake, IIM Rohtak, and the University of Auckland. His research focuses on intelligent systems, deep learning, and cyber resilience. He has been recognized internationally with awards and honors such as the South Korean Research Society Award, the Sentinels of Science Award, and inclusion in Marquis Who’s Who in the World. He has also served as an editor and reviewer for top-tier journals, and as a grant panellist for DAAD-Germany and the Swiss National Science Foundation. His contributions continue to advance the global frontiers of intelligent and secure computing.

Profiles: Google Scholar | Scopus

Featured Publications

Raheja, J. L., Chaudhary, A., & Singal, K. (2011). Tracking of fingertips and centers of palm using KINECT. 2011 IEEE 3rd International Conference on Computational Intelligence, Modelling and Simulation (CIMSIM), 248–252.

Pandy, H., Chaudhary, A., & Mehrotra, D. (2014). A comparative review of approaches to prevent premature convergence in GA. Applied Soft Computing, 24, 1047–1077.

Chaudhary, A., Raheja, J. L., Das, K., & Raheja, S. (2011). Intelligent approaches to interact with machines using hand gesture recognition in natural way: A survey. International Journal of Computer Science and Engineering Survey (IJCSES), 2(1), 122–133.

Raheja, J. L., Kumar, S., & Chaudhary, A. (2013). Fabric defect detection based on GLCM and Gabor filter: A comparison. Optik, 124(23), 6469–6474.

Raheja, J. L., Mishra, A., & Chaudhary, A. (2016). Indian Sign Language recognition using SVM. Pattern Recognition and Image Analysis, 26(2), 434–441.

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