Computer Science, The University of Texas at Austin. BS expected May 2028.
Daniel Lam
Computer Science, UT Austin, May 2028Research Assistant, RobIn Lab
I work where robot learning meets production AI software.
I'm a computer science student at UT Austin concentrating in AI and robotics. In the Robotic Interactive Intelligence Lab with Prof. Roberto Martín-Martín, I study how robots can manipulate objects without breaking them, and I led the RoboCasa implementation of OopsieVerse (RSS 2026).
On the engineering side I build AI agents that ship: voice and multi-agent planning on Salesforce Agentforce in summer 2026, and LLM developer tools for simulation engineers at Lockheed Martin in 2025.
I also lead simulation for Texas Marine Robotics' RoboBoat 2027 boat and mentor new researchers through Texas Robotics. Off the clock I travel with a camera; those photos live on the Shots page.
Recent
OopsieVerse accepted to RSS 2026.
Joined Salesforce Agentforce as a software engineer intern.
Started leading simulation for Texas Marine Robotics.
Became a peer mentor for robot learning at Texas Robotics.
研究Research
Robot manipulation safety, simulation, and perception.
OopsieVerse overview. Video: RobIn Lab
OopsieVerse overview. Video: RobIn Lab
RSS 2026Paper
OopsieVerse: A Safety Benchmark with Damage-Aware Simulation for Robot Manipulation
A simulator-agnostic framework that turns contact forces, heat, and liquid into measurable damage, plus 32 household tasks that pit easy-but-risky strategies against careful ones.
My part Led the RoboCasa implementation: 23 damageable objects, 16 kitchen environments, and 15 long-horizon tasks with staged subgoal checks.
An OpenCV heads-up display that shows teleoperators each object's live health while they record. It made 450+ safety-annotated demonstrations across 32 tasks possible, and damage-aware imitation learning trained on them cut real-world damage on a Franka Panda by 60%.
Rendering full course scenes in NVIDIA Isaac Sim to auto-label buoy images, so the detector on the boat's Jetson Nano trains without on-water labeling.
Publications
RSS 2026
OopsieVerse: A Safety Benchmark with Damage-Aware Simulation for Robot Manipulation. A. Balaji*, A. Bahety*, S. Ambatipudi, D. Lam, J. Xu, R. Martín-Martín. Robotics: Science and Systems, 2026. * equal contribution