Ms. Shaguna Gupta | Cloud Computing Computer Science Research | Best Researcher Award

National College of Ireland | Ireland

Shaguna Gupta is a dedicated computer science researcher specializing in cloud computing, distributed systems, and intelligent transportation systems. She is currently pursuing her Ph.D. at Trinity College Dublin (TCD), Ireland, focusing on highway traffic flow optimization using deep reinforcement learning to improve traffic throughput and travel time reliability. She holds a Master of Technology in Cloud Computing with Queuing Theory from Shri Mata Vaishno Devi University (SMVDU), India, and a Bachelor of Engineering from Jammu University, India. Her research experience spans multiple international institutions, including a postgraduate studentship under Science Foundation Ireland’s CRT ADVANCE project, a research internship at the University of Virginia, USA, and project work at the Indian Institute of Science, Bangalore. She has contributed to multiple publications in areas such as rideshare optimization, queuing theory for cloud services, and microservice resilience. As an educator, she has served as an associate faculty member, demonstrator, and lecturer, supervising cloud computing projects and teaching modules on AI, programming, and cybersecurity. Her research interests include cloud computing, traffic management, multi-agent reinforcement learning, and distributed systems. She has received several academic awards, including gold medals, scholarships, and best paper presentations. Committed to advancing technology for societal benefit, she actively participates in workshops, conferences, and community outreach, reflecting a balance of innovation, leadership, and practical impact.

Profile: Google Scholar

Featured Publications

Gupta, S., Narang, R., Krishnaswami, K., & Yadav, S. (1994). Plasma selenium level in cancer patients. Indian Journal of Cancer, 31(3), 192–197.

Fusco, V. F., Sancheti, S., & Gupta, S. (1994). Active antenna element design issues. IEE Colloquium on Smart Antennas (Digest No: 1994/182), 9/1–9/7.

Gupta, S., & Fusco, V. F. (1996). Low cross-polarized integrated mixer/phase shifter patch antenna for beamforming applications. 26th European Microwave Conference, 1, 397–400.

Gupta, S., & Pourush, R. K. S. (1999). Technical Notes-4 x 4 planar phased array of circular patch microstrip antenna in plasma environment for on-board applications. Space Technology-Abingdon, 19(2), 97–108.

Gupta, S., Fusco, V. F., & Sancheti, S. (1999). Self-phased re-transmitting integrated mixer antenna array. International Journal of Electronics, 86(2), 207–215.

Gupta, S., Narang, R., & Patel, M. K., Gupta, K., Kumar, K. (2025). Enhanced ECC-driven text encryption scheme using chaotic maps and Rhotrices. Palestine Journal of Mathematics, 14(3).

Gupta, S., & Arora, S. (2018). Queueing system in cloud services management: a survey. International Journal of Pure and Applied Mathematics, 119(12), 12741–12753.

Shaikh, R. (2025). Prediction of resource utilization in cloud computing using machine learning. Dublin, National College of Ireland.

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

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