Dr. Vivek Yelleti is an Assistant Professor in the Information Systems and Business Analytics area. He received his Ph.D. in Computer Science and Engineering from the National Institute of Technology (NIT) Warangal in association with the Institute for Development and Research in Banking Technology (IDRBT), Hyderabad. His doctoral research focused on developing scalable feature selection methodologies using evolutionary computing techniques for Big Data environments. Prior to his Ph.D., he obtained an M.Tech. in Computer Science from the University of Hyderabad and a B.Tech. in Computer Science and Engineering from JNTU- Gurajada, Vizianagaram.
His research lies at the intersection of Artificial Intelligence, Machine Learning, Big Data Analytics, Evolutionary Computing, Explainable AI, Financial Analytics, and Agentic AI Systems. Over the years, he has developed novel methodologies for fraud analytics, feature engineering, predictive modeling, financial forecasting, federated learning, adversarial machine learning, and large language model (LLM)-driven software engineering. His research aims to build scalable, interpretable, and trustworthy AI systems capable of addressing real-world challenges in banking, finance, cybersecurity, healthcare, and business decision-making.

Dr. Vivek has published more than 36 research papers, including 13 journal articles and 23 conference publications in leading international journals and premier CORE-ranked conferences. His work has appeared in prestigious venues such as ACM Computing Surveys, Swarm and Evolutionary Computation, Expert Systems with Applications, Cluster Computing, Quantum Information Processing, and Computers & Electrical Engineering. His research has advanced the fields of evolutionary computing, scalable machine learning, fraud analytics, financial forecasting, causal inference, explainable AI, and data-driven decision-making systems.
Before joining academia as a faculty member, he served as a Postdoctoral Fellow at NIT Warangal and as a Research Fellow at IDRBT, where he worked on several industry-sponsored and government-funded projects in collaboration with banks, financial institutions, and technology organizations. His contributions include the development of explainable fraud detection frameworks, privacy-preserving federated learning systems, adversarial machine learning solutions, and AI-driven decision support systems.
Dr. Vivek is actively involved in mentoring undergraduate and postgraduate students and has guided research projects spanning machine learning, financial analytics, graph neural networks, computer vision, reinforcement learning, and large language models. He is also a reviewer for several reputed international journals published by ACM, Elsevier, Springer, and IEEE.