I am currently a Research Scientist at Meta. I received my PhD studying robotics & AI in the Stanford ARMLab, where I was advised by Monroe Kennedy III. My doctoral research centered on developing cooperative robotic agents for human-robot tasks. I was supported by the NSF Graduate Research Fellowship.

Previously, I was advised by Nanshu Lu as an undergraduate at UT Austin.

[CV] [Github] [LinkedIn] [eleyng [at] stanford [dot] edu]

News:

• 10/18/23 Our latest work, Diffusion Co-Policy for Synergistic Human-Robot Collaborative Tasks, has been accepted to RA-L!
• 7/1/23 My thesis, titled “Long-horizon prediction for human-robot collaboration”, is now available online!
• 2/21/23 Excited to release the repository for the cooperative table-carrying task, a cooperative multi-agent continuous state-action gym environment! Feel free to check it out, and consider using it to benchmark your cooperative algorithms.
• 2/19/23 Code for the cooperative planner has been released.
• 1/16/23 My paper, “It Takes Two: Learning to Plan for Human-Robot Cooperative Carrying”, has been accepted to ICRA 2023 in London, UK!
• 6/11/22 My work on “Learning Action and State Sampling Distributions for Human-Robot Collaboration”, has been accepted to the Workshop on Learning from Diverse, Offline Data (L-DOD) at RSS 2022.