RA-L · IROS 2025
(robot = continual+generative+reinforcement) * learning
Alan Chen
I teach robots to build things.
Undergrad researcher at UT Austin (Turing Scholars), working on RL for vision-language-action models at the Learning Agents Research Group. Previously at CMU's Robotics Institute, where I published on robotic assembly before finishing high school.
currently
Learning Agents Research Group · UT Austin
RL for vision-language-action models
Fine-tuning robot foundation models (Octo, OpenVLA) with PPO, GRPO, and Diffusion-PPO for mobile manipulation in ManiSkill.
Arm · Central Engineering AI · Summer 2026
LLM Research Engineering Intern
Just wrapped up: independently developed a recursive language model approach and analyzed complex workloads to optimize uArch.
selected research
Robots that build things
Deep RL for robots that plan and build in the physical world: assembly planning, learning from demonstration, and policies that respect physics.
incomplete
inferred target
completed by the agentMECC 2025
AssemblyComplete: 3D Combinatorial Construction with Deep Reinforcement Learning
arXiv 2023
Simulation-Aided Learning from Demonstration for Robotic LEGO Construction
writing
Notes & writeups
· 1 min
Rebuilding this site (and how writing works here now)
This site is a pile of Markdown files now. The old version was a React app, and adding anything meant editing components. By the time I finished fiddling with JSX, I didn’t feel like writing anymor…
· 3 min
Move 37, Move 78
My new revamped website’s homepage animation replays the opening of Game 4 of Lee Sedol vs. AlphaGo and stops at Move 78 which is arguably one of the most famous moves played by a human, a wedge th…
note · · 6 min
Probability, likelihood, and measure
Why probability and likelihood are different objects, what MLE is actually doing, and the measure-theory vocabulary that makes densities, PMFs, and Dirac deltas one thing.
beyond the lab
Say hi
Always happy to talk robots, RL, Go, or whatever.