Correspondence-Oriented Imitation Learning: Flexible Visuomotor Control with 3D Conditioning
We propose a method for learning robot manipulation policies in a self-supervised manner using a flexible 3D-based task representation.
Oct 30, 2025
UniEnv
A new unified robot learning framework supporting multiple tensor and simulation backends. Currently in the works, will be released in 2025.
Jul 11, 2025
Cornell CS4756/5756: Robot Learning
Cornell CS4756 is an undergrad/graduate-level course on robot learning algorithms and techniques. The course covers a wide range of topics in deep learning, imitation learning, reinforcement learning, representation learning and robotics.
Jan 20, 2025
Cornell CS6758: Deep Learning for Robotics
Cornell CS6758 is a graduate-level course on deep learning for robotics. The course covers a wide range of topics in deep learning, reinforcement learning, and robotics, with a focus on the intersection of these fields.
Aug 24, 2024
Grow Your Limits: Continuous Improvement with Real-World RL for Robotic Locomotion
We propose a method for dynamically adjusting a robot’s exploration while learning in the real world. We demonstrate that growing the limits of the robot’s search space leads to safer, more efficient learning and enables continuous improvement.
May 13, 2024
ROAR_PY
I led the training and evaluation of a RL-based autonomous racing policy in the Carla Simulator. The agent can drive at 150 km/h in the simulator. In the process, I led the development of ROAR-PY: A streamable, gymnasium compatible control suite that unifies control of vehicles / reading of sensors in simulation and in real world for any autonomous vehicles.
Jun 15, 2023
DarBots
I was very fortunate to gain early exposure to robotics through the DarBots program at Darlington School. I competed as the team captain in the FTC robotics competition for two years.
May 20, 2020