Zixuan Huang

I am Zixuan Huang, a third year PhD student in Robotics at University of Michigan studying learning for robot manipulation. I'm very fortunate to be advised by Prof. Dmitry Berenson. Prior to UMich, I was a Master student in Robotics at Carnegie Mellon University advised by Prof. David Held.

I obtained a B.S. in Computer Science from the City University of Hong Kong, where I explored privacy-preserving machine learning and non-photorealistic rendering under the supervision of Prof. Antoni B. Chan, Prof. Cong Wang and Prof. Jing Liao

CV  /  Github  /  Google scholar

Email: zixuanh[at]umich.edu

My current research focuses on the intersection of robotics, computer vision, reinforcement learning and planning. My goal is to enable robot to learn, adapt and operate autonormously in the unstructured envrionments.

We enable the robot to reason about the changing contacts between objects and environment by predicting a sequence of NDF point clouds.

We use diffusion model to generate subgoals at appropriate temporal resolution dynamically to guide MPC

Learning a particle-based dynamics model on the visible part of the cloth enables efficient planning for cloth smoothing. We show that implicit occlusioning by graph imitation further improves the performance.

A framework for semantic style transfer by patch attention.

Awesome template stolen from Jon Barron