Developed UCLID (one of the first satisfiability modulo theories (SMT) solvers and SMT-based verifiers) and continues to work on new SMT solvers (e.g., Algaroba). Contributed to fundamental techniques in algorithmic formal synthesis, including counterexample-guided inductive synthesis (CEGIS), syntax-guided synthesis (SyGuS), and more. The research has been applied to software, hardware, distributed systems, AI/ML, robotics, cyber-physical systems, and biological systems.
Research Experience
Cadence Founders Chair Professor at the Department of Electrical Engineering and Computer Sciences and Group in Logic and the Methodology of Science, University of California, Berkeley. Affiliated faculty member of the Industrial Cyber-Physical Systems Center, Berkeley AI Research, and the Simons Institute for the Theory of Computing.
Background
Research interests include the intersection of formal methods and artificial intelligence/machine learning, with a focus on ensuring that computational systems are provably safe, secure, and trustworthy. Specializes in formal methods, automated reasoning, AI/ML, etc.