Gautam Biswas, Ph.D.
Cornelius Vanderbilt Professor of Computer Science and Computer Engineering
Overview of Interests
Gautam Biswas holds an Endowed Chair as Cornelius Vanderbilt Professor of Computer Science and Computer Engineering, in the EECS Department and a Senior Research Scientist at the Institute for Software Integrated Systems (ISIS) at Vanderbilt University. Biswas conducts research in Intelligent Systems with primary interests in hybrid modeling, simulation, and analysis of complex embedded systems, and their applications to diagnosis, prognosis, and fault-adaptive control. As part of this work, he has worked on fault diagnosis and fault-adaptive control of secondary sodium cooling systems for nuclear reactors, automobile engine coolant systems, fuel transfer systems for aircraft, Advanced Life Support systems and power distribution systems for NASA. He has also initiated new projects in health management of complex systems, which includes online algorithms for distributed monitoring, diagnosis, and prognosis. In other research projects, he is involved in developing simulation-based environments for learning and instruction. The most notable project in this area is the Teachable Agents project, where students learn science by building causal models of natural processes. More recently, he has exploited the synergy between computational thinking ideas and STEM learning to develop systems that help students learn science and math concepts by building simulation models. He has also developed innovative educational data mining techniques for studying students’ learning behaviors and linking them to metacognitive strategies. In all of his projects, there has been a strong emphasis on scaffolding students’ learning of metacognitive strategies, and preparing them for future learning. In collaboration with other Vanderbilt Kennedy Center investigators, he is interested in tailoring his learning environments for STEM learning to help children with special needs learn subject matter as well as regulatory processes, such as affect and metacognition. His work in machine learning and data mining is broadly applicable to a large number of projects that may require exploratory data nalysis methods. His research has been supported by funding from the Army Research Labs, NASA, NSF, DARPA, and the US Department of Education. His industrial collaborators include Airbus, Honeywell Technical Center, and Boeing Research and Development.