AI Software Engineer · Robotics Simulation · Robot Learning
Building simulation environments and training robot policies for manipulation, then studying what they can retain, transfer, and reuse when the task or domain changes.
Explore some recent work
Force-Aware Peg Insertion
4 PPO policy variants, 3 seeds each: force observation roughly doubled task success, from 7.3% to 14.2%.
Isaac LabPPORL-Games
Code ↗OpenUSD Digital-Twin Pipeline
Git-versioned Isaac Sim workspace, scenes as diffable USD text, driven from a local agent.
Isaac SimOpenUSDDocker
Code ↗InstruX
Orchestrates across 6 tools (Isaac Sim, Isaac Lab, Cosmos, Omniverse, OpenUSD, and ROS2) into one robot-policy decision layer.
Isaac SimIsaac LabOpenUSD
Live ↗Direction
My direction is robot learning through simulation: building manipulation environments, training policies, and studying how learned skills can transfer across tasks, objects, and domains instead of being relearned from scratch. Full background on the CV.