Dr. Swarat Chaudhuri works in the intersection of formal methods and artificial intelligence (AI). He received his bachelor of technology in computer science from the Indian Institute of Technology Kharagpur. He completed a doctorate in philosophy in computer science at the University of Pennsylvania. Dr. Chaudhuri was previously a faculty member at Pennsylvania State University and Rice University, has taught a wide range of undergraduate and graduate courses on computer science, and has a long track record of federally funded research. His accolades include an NSF CAREER award, a Google Research Award, the ACM SIGPLAN John Reynolds Doctorate Dissertation Award, and multiple distinguished paper awards.

His research vision is to build a new generation of AI systems that are designed from the ground up with the goals of reliability, transparency, and security. He seeks to realize this vision through a synthesis of ideas from programming languages, formal methods, and machine learning.

He is a member of UT Austin's Programming Languages and Formal Methods group, a core faculty member in UT's Machine Learning Laboratory, and an affiliate of Texas Robotics.