Robot Learning

Develop and optimize a learning-based robotic manipulation control stack, including teleoperation with smooth, low-latency motion. Train policies for manipulation and locomotion using reinforcement learning and imitation learning, then deploy them while diagnosing latency and bottlenecks. Minimize the sim-to-real gap by co-optimizing simulation and real-world robot behavior, collaborating with a team building general-purpose Physical AI.