Biography

Soham Das is an Assistant Professor in the Department of Industrial and Systems Engineering at the University of Tennessee, Knoxville, where he is part of the Science-Informed Artificial Intelligence cluster and leads the Multiagent Systems and Complexity Group. He received his Ph.D. in Operations Research from Texas A&M University, College Station, TX in 2025.

His research develops mathematical foundations for multiagent systems by integrating game theory, optimization and reinforcement learning. He studies how multiple autonomous decision makers can safely and efficiently learn, adapt, and compete in dynamic and uncertain environments.

His work spans constrained and stochastic games, multiagent reinforcement learning, information design, and network optimization, with applications in energy systems, autonomous robotics, healthcare, and large-scale networked systems. His long-term goal is to develop principled theory for scalable and trustworthy multiagent intelligence.

His research has been recognized with awards such as the IEEE Control Systems Society Outstanding Student Paper Prize, the IISE Transactions Best Application Paper Award, etc. He is a member of IEEE, INFORMS, and SIAM.


Education

• PhD, Operations Research, Texas A&M University, 2025
• B.Tech. in Mechanical Engineering, National Institute of Technology Durgapur, 2017/li>

Courses Taught

• IE 560 – Introduction to Proofs for Engineers
• IE 310 – Operations Research II – Probabilistic Models

Education

• Panelist, Preparing for the Job Market (Academia, Industry, and National Labs), IISE Annual Conference & Expo, 2026.
• Reviewer for leading journals and conferences in control, optimization and learning.

Awards & Recognitions

• IISE Transactions Best Application Paper Award (2026)
• IEEE Control Systems Society Outstanding Student Paper Prize, TC Network Systems (2025)
• Texas A&M Informs Student Chapter Poster Competition Winner (2024)