Ziwen Zhuang (庄子文)
I am a first-year PhD student at IIIS, Tsinghua Univesity, working on Athletic Intelligence, Embodied AI, and Robotics. I am currently working as a research assistant at Shanghai Qi Zhi Institute, advised by Professor Hang Zhao. Before that, I was a member of the MARS Lab at ShanghaiTech University, advised by Professor Soeren Schwertfeger. I tightly collaborate with students at Stanford University and Carnegie Mellon University.
I have participated in several competitions: CMCM, MCM, RoboMaster. I was the project manager in the ShanghaiTech RoboMaster team.
News
2024-04: Invited talk at China Embodied AI Conference
2023-11: Invited talk at TechBeat
2023-08: Our paper “Robot Parkour Learning” is accepted by CoRL 2023. Project Page
Publications
Humanoid Parkour Learning Permalink
Published in , 2024
A single vision-based end-to-end whole-body-control parkour policy for humanoid robots. 
Recommended citation: Ziwen Zhuang, , Shenzhe Yao, and Hang Zhao. "Humanoid Parkour Learning." (2024).
Robot Parkour Learning Permalink
Published in CoRL (Oral) Best system paper finalist, 2023
An end-to-end neural network for Quadruped robot with extreme agility skills 
Recommended citation: Ziwen Zhuang*, Zipeng Fu*, Jianren Wang, Christopher G Atkeson, Soren Schwertfeger, Chelsea Finn, & Hang Zhao (2023). Robot Parkour Learning. In 7th Annual Conference on Robot Learning.
Semi: Self-supervised exploration via multisensory incongruity.
Published in ICRA, 2022
A self-supervised exploration algorithm that uses multimodal sensory input as a reward signal. 
Recommended citation: Jianren Wang*, Ziwen Zhuang*, and Hang Zhao. Semi: Self-supervised exploration via multisensory incongruity. International Conference on Robotics and Automation, 2022. https://arxiv.org/abs/2009.12494
Adversarially Robust Imitation Learning Permalink
Published in CoRL, 2021
Imitation Learning, Adversarial Learning
Recommended citation: Jianren Wang*, Ziwen Zhuang*, Yuyang Wang, and Hang Zhao. Adversarially robust imitation learning. In 5th Annual Conference on Robot Learning, 2021. https://openreview.net/forum?id=9aVCUv3nKBg