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Gautam Biswas

Cornelius Vanderbilt Professor of Engineering
Professor of Computer Science
Professor of Computer Engineering
Professor of Engineering Management

Electrical Engineering and Computer Science

Intellectual Neighborhoods

Research Focus

Model- and Data-Driven methods for Monitoring, Control, Diagnostics, Prognostics, and Fault tolerance in Cyber Physical Systems, Reinforcement Learning, Intelligent Learning Environments, Learning Analytics, Integrated Planning, Scheduling, Control, and Resource Allocation for Complex systems


Gautam Biswas is a Cornelius Vanderbilt Professor of Engineering, and Professor of Computer Science, Computer Engineering, and Engineering Management in the EECS Department. He also is a Senior Research Scientist at the Institute for Software Integrated Systems. He has an undergraduate degree in Electrical Engineering from the Indian Institute of Technology (IIT) in Mumbai, India, and M.S. and Ph.D. degrees in Computer Science from Michigan State University in E. Lansing, MI.

Prof. Biswas conducts research in Intelligent Systems with primary interests in monitoring, control, and fault adaptivity of complex cyber physical systems. In particular, his research focuses on Deep Reinforcement Learning, Unsupervised and Semi-supervised Anomaly Detection methods, and Online Risk and Safety analysis applied to Air and Marine vehicle as well as Smart Buildings. His work, in conjunction with Honeywell Technical Center and NASA Ames led to the NASA 2011 Aeronautics Research Mission Directorate Technology and Innovation Group Award for Vehicle Level Reasoning System and Data Mining methods to improve aircraft diagnostic and prognostic systems.

In other research, Prof. Biswas is involved in developing intelligent open-ended learning environments focused on learning and instruction in STEM domains. He has also developed innovative learning analytics and data mining techniques for studying students’ learning behaviors and linking them to their metacognitive and self-regulated learning strategies. His research has been supported by funding from the Army, Navy, NASA, NSF, DARPA, and the US Department of Education. He has published extensively, and currently has over 600 refereed publications.

Dr. Biswas is an associate editor of the IEEE Transactions on Learning Technologies, the Internal Journal of Prognostics and Health Management. He also is on the editorial board of International Journal of Artificial Intelligence in Education. He has served on the Program Committee of a number of conferences, and currently is serving on the Executive committee of the Asia Pacific Society for Computers in Education. He is a Fellow of the IEEE Computer Society and the Prognostics and Health Management society.