Ziwen Zhuang (庄子文)

I am a second-year graduate student as well as Computer Science researcher focusing on Artificial General Intelligence, Embodied AI, and Robotics. I am currently working as a research assistant at Shanghai Qi Zhi Institute, advised by Professor Hang Zhao. I am also 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.

In order to reach AGI, my research interest mainly focus on the two aspects of robot learning:

1. Cognitive Intelligence: Learn real-world relation model through interacting with the world (self-supervised exploration and learning)

2. Athletic Intelligence: Designing a general learning algorithm that can solve as many robotics control problems as possible. Also co-optimizing the robot hardware and software to achieve better performance. Especially Humanoid and Quadruped robots.

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

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