Yilang Liu

Ph.D. Candidate, Mechanical Engineering • Yale University

Yilang Liu

Hi! I'm a Ph.D. candidate in Mechanical Engineering at Yale University, advised by Prof. Ian Abraham. My research focuses on robotics, optimal control, and reinforcement learning, with an emphasis on sample-based control, visual policy learning, and legged locomotion.

Previously, I received my M.S. from Carnegie Mellon University and dual B.E./B.S. degrees from Chongqing University and the University of Cincinnati. I have also worked as a robotics intern at Dexmate Inc.

Research

I'm interested in robotics, optimal control, reinforcement learning, and vision-based policy learning. My research develops sample-based and data-driven methods for robot control, with applications in legged locomotion, dexterous manipulation, and autonomous exploration.

News

  • 05/2026: Our paper Asymptotically Optimal Ergodic Coverage on Generalized Motion Fields was accepted to RSS 2026.
  • 01/2026: Our paper Sample-Based Hybrid Mode Control was accepted to ICRA 2026.
  • 09/2025: Our paper Accelerating Visual-Policy Learning through Parallel Differentiable Simulation was accepted to NeurIPS 2025 as a Spotlight.

Selected Publications

Services

Reviewer

IEEE Robotics and Automation Letters (RA-L); ICRA 2022–2026; IROS 2022–2026; ECCV 2024; RSS 2025.