Tairan's research focuses on developing scalable learning-based control methods for humanoid robots, aiming to achieve human-level athletic skills and semantic intelligence. He works on whole-body control, sim-to-real learning, and human-to-humanoid teleoperation, leveraging large-scale computation and data to enable adaptive, generalizable, and agile robotic behavior.
Tairan is a second-year Ph.D. student at Carnegie Mellon University’s Robotics Institute, advised by Guanya Shi and Changliu Liu. He is also a member of NVIDIA’s GEAR group, led by Jim Fan and Yuke Zhu. He received his Bachelor’s in Computer Science from Shanghai Jiao Tong University. His research is supported by the NVIDIA Graduate Fellowship and the CMU RI Presidential Fellowship.