Gautam Biswas
Cornelius Vanderbilt Professor of Engineering; Professor of Computer Science, Electrical and Computer Engineering
Senior Research Scientist
Gautam 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 vehicles 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.
His research is supported by funding from the Army, NASA, and NSF. He has published extensively and currently has over 600 refereed publications. He is a Fellow of the IEEE Computer Society, Asia Pacific Society for Computers in Education, and the Prognostics and Health Management society.
Projects
- Analyzing and Supporting Students' Learning Behaviors in Computational STEM Learning Environments
- Collaborative Research: Computational Modeling for Integrating Science and Engineering Design (CMISE): Model Construction, Manipulation, and Exploration
- Demonstration of the In-Time Learning-Based Safety Management for Scalable Heterogeneous AAM Operations
- FW-HTF Theme 1: Collaborative Research: Augmenting and Advancing Cognitive Performance of Control Room Operators for Power Grid Resiliency
- Combatant Craft Health Monitoring System
- Combining Real-time & Offline Decision Making for Urban Air Mobility Systems
- Digital Twin Technologies to Improve Mission Readiness and Sustainment
- Implementing Betty's Brain in the PILA Environment
- Multi-level Learner Modeling for Land Navigation Training Applications
- Science Projects Integrating Computing and Engineering (SPICE)
- FW-HTF Theme 1: Collaborative Research: Augmenting and Advancing Cognitive Performance of Control Room Operators for Power Grid Resiliency
- Analyzing and Supporting Students' Learning Behaviors in Computational STEM Learning Environments
- Analysis and Evaluation of Autonomous Decision-Making Algorithms on Resource-Constrained Processors
- Collaborative Research: An Interdisciplinary Approach to Prepare Undergraduates for Data Science Using Real-World High Frequency Data
- Demonstration of the In-Time Learning-Based Safety Management for Scalable Heterogeneous AAM Operations
- Multimodal Analytics for Learner Modeling and After-Action Review in Synthetic Training Environments
- NSF EAGER: Co-Designing a Cognitive Teaching Assistant to Support Evidence-Based Instruction in Open-Ended Learning Environments
- Collaborative Research: Computational Modeling for Integrating Science and Engineering Design (CMISE): Model Construction, Manipulation, and Exploration
- AI Institute: The Institute for an AI-Engaged Future of Learning
Areas of Expertise
Artificial Intelligence, Machine Learning, Reinforcement Learning Monitoring, Diagnosis, Fault-Adaptive Control of Cyber-Physical Systems Intelligent Learning Environments for K-12 STEM+C Education Multimodal Learning Analytics