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