Mohammad Ahmadi

Mohammad Ahmadi, Ph.D.  joined the Department of Industrial and Systems Engineering at Mississippi State University in 2026. He earned his Ph.D. in Systems and Industrial Engineering and M.S. in Statistics and Data Science from the University of Arizona, as well as his M.S. in Industrial Engineering–Systems Optimization and B.S. in Industrial Engineering from K. N. Toosi University of Technology.

His research focuses on developing computationally efficient algorithms with theoretical convergence and complexity guarantees for large-scale and hierarchical optimization problems. His primary research interests include bilevel optimization, saddle-point problems, stochastic optimization, and first-order methods, with applications in artificial intelligence and machine learning.

His research explores applications in adversarial learning, multi-task learning, and large language model (LLM) unlearning. He also has research and industry experience in AI-driven healthcare analytics, statistical quality control, and machine learning applications in engineering systems. His emerging research interests include developing computationally efficient and reliable AI algorithms for resource-constrained devices and edge computing.

Dr. Ahmadi serves as an Academic Editor for Computational Research Progress in Applied Science & Engineering and as a reviewer for several journals and conferences, including NeurIPS, Computers & Industrial Engineering, Scientific Reports, and Quality & Quantity.