Shuo Cheng

What should transfer from a human video to a robot?
Human2Any learns how objects interact, then adapts that knowledge through test-time reasoning and planning.
Accepted to #CoRL2026! I'll be presenting in person next week—come say hi!
human2any.github.io (1/n)

Can large-scale sim data enable real-world generalization?🤔
In our new work, we introduce a generalizable domain adaptation setting, where policies must handle real-world situations never presented in the real training data. (1/n)

Can we teach a robot hundreds of tasks with only dozens of demos?
Introducing NOD-TAMP: A framework that chains together manipulation skills from as few as one demo per skill to compositionally generalize across long-horizon tasks with unseen objects and scenes. (1/N)

Come join us for an exciting RSS hybrid workshop focused on Learning for Task and Motion Planning featuring an incredible line-up of speakers and panels. Don't miss out on the chance to submit your work (deadline May 19th)! zt-yang.github.io/rss23-l4tamp-w…

Introducing LEAGUE - Learning and Abstraction with Guidance! LEAGUE is a new framework that uses symbolic skill operators to guide skill learning and state abstraction, allowing it to solve long-horizon tasks and generalize to new tasks and domains. Joint work with @danfei_xu 1/6