Research
My research focuses on learning-based control and perception for legged robots, particularly robust locomotion, visual obstacle traversal, agile navigation, and sim-to-real deployment.
Research Areas
Robust Quadrupedal Locomotion
Learning robust locomotion policies for legged robots operating across diverse terrains and disturbances.
Visual Locomotion and Navigation
Integrating exteroceptive perception with control for obstacle traversal and agile navigation.
World Models for Robot Control
Learning predictive world models that capture terrain and body dynamics for planning and closed-loop control.
Reinforcement Learning for Robotics
Designing reward structures, curricula, and training pipelines that turn reinforcement learning into deployable robot skills.
Sim-to-Real Deployment
Bridging simulation and physical robots through system validation, deployment tooling, and real-world experimentation.
Current Work
Current research topics will be added as the work progresses.
Publications
Peer-reviewed papers and technical reports.
Publications and technical reports will be added here.
Research Notes
Informal write-ups on methods, experiments, and lessons learned.