Ting Wu

Real-world tennis serving by humanoid robots is now possible without motion capture, thanks to a novel adaptive framework that learns directly from video.

HiPHI significantly expands the diversity of human motion data, offering a game-changing resource for training humanoid AI in complex real-world tasks.

Achieving optimal regret in generalized linear bandits with heavy-tailed noise using a novel one-pass update algorithm could revolutionize decision-making in dynamic environments.

Achieving a staggering 98.7% success rate in humanoid loco-manipulation by seamlessly chaining meta-skills through a novel contact flow representation.

Bipedal soccer robots can now autonomously recover from falls in under a second thanks to a novel RL framework.