Research Areas
Reinforcement Learning
Data-efficient RL, active learning, exploration,
decision‑making for science and environment
Robotics
Scalable simulation, physics-informed reasoning, multimodal sensing, mobile manipulation
Hardware Design
Co-design for robot hardware and policy learning, design space exploration for AI accelerators