MTS, Robot Learning

Build and optimize a learning-based robotic manipulation control stack, including teleoperation for smooth, low-latency motion. Train manipulation and locomotion policies using reinforcement learning and imitation learning, then deploy them and diagnose performance bottlenecks. Improve real-world results by minimizing the sim-to-real gap through co-optimizing simulation and robot behavior, working with a team focused on general-purpose Physical AI.