Area of research
Artificial Intelligence · Computational Theory and Mathematics
Research interest
Research interests include Formal Methods in Verification, Reinforcement Learning in Robotics, Logic, programming, and type systems, and Adversarial Robustness in Machine Learning.
Safe Control With Learned Certificates: A Survey of Neural Lyapunov, Barrier, and Contraction Methods for Robotics and Control
A Neural Lyapunov Approach to Transient Stability Assessment of Power Electronics-Interfaced Networked Microgrids
SP&R: SMT-Based Simultaneous Place-and-Route for Standard Cell Synthesis of Advanced Nodes
Interpolants in Nonlinear Theories Over the Reals
SMT-Based Nonlinear PDDL+ Planning