I am a research scientist at NVIDIA AI. My primary focus is to develop generally capable autonomous agents. To tackle this grand challenge, my research efforts span foundation models, policy learning, robotics, multimodal learning, and large-scale systems. I obtained my Ph.D. degree at Stanford Vision Lab, advised by Prof. Fei-Fei Li. Previously, I did research internships at NVIDIA, Google Cloud AI, OpenAI, Baidu Silicon Valley AI Lab, and Mila-Quebec AI Institute. I was the Valedictorian of Class 2016 and a recipient of the Illig Medal at Columbia University. Feel free to follow me on for latest research announcements and team updates!
Nov. 2022: has won 🎉 Outstanding Paper Award 🎉 at NeurIPS [announcement]! I am also invited as a Speaker at the 1st NeurIPS Foundation Model for Decision Making (FMDM) workshop — please join us at New Orleans!
Oct. 2022: We trained a transformer called VIMA that ingests multimodal prompt and outputs controls for a robot arm. A single agent is able to solve visual goal, one-shot imitation from video, novel concept grounding, visual constraint, etc. Strong scaling with model capacity and data! We open-source everything: code, pretrained models, training dataset, and simulation benchmark. Check out our paper and website!
Jun. 2022: has launched! MineDojo is a new framework for building generally capable agents with internet-scale knowledge in Minecraft. Paper, code, and databases are all open access. Check it out today!
Ph.D. in Computer Science, 2016 - 2021
Stanford University
B.S. in Computer Science, 2012 - 2016
Columbia University, Summa Cum Laude
Valedictorian of Class 2016
Columbia University
Research Highlights
Visit my Google Scholar page for a comprehensive listing!