尚靖桓 Jinghuan Shang
I'm a Ph.D. candidate in the Department of Computer Science at Stony Brook University, working with Prof. Michael Ryoo, as a part of CV Lab at Stony Brook. I received my Bachelor's degree from IEEE Honored Class at Shanghai Jiao Tong University (SJTU) in 2018, with honor from Shanghai.
Research interest: Representation Learning, Robotics, and Computer Vision. Specifically, I find good visual representations for robots to perform visual tasks under reinforcement learning and imitation learning settings.
[CV][GitHub][Notes(*new!)] Email: jishang [at] cs &dot& stony brook %dot% edu
2022/09 - 3DTRL and Study on SSL+RL are accepted to NeurIPS 2022.
2022/09 - TRITON for robot sim2real is accepted to CoRL 2022.
2022/09 - StARformer for real robot is accepted to TPAMI. A cute ground mobility robot is able to continuously follow me purely by visual inputs.
2022/08 - Started a research internship at Motional.
2022/07 - StARformer is accepted to ECCV 2022. Local representations benefit long-term sequence modeling in vision-based RL.
2022/06 - Introducing 3D Token Representation Layer, a plug-and-play module for Transformer to learn viewpoint-agnostic representations.
2021/06 - Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?
2021/06 - Our paper on Third-Person Imitation Learning is accepted to IROS 2021.
Learning Viewpoint-Agnostic Visual Representations by Recovering Tokens in 3D Space
Jinghuan Shang, Srijan Das, and Michael S. Ryoo
[Project Page] [Code] [arXiv]
Does Self-supervised Learning Really Improve Reinforcement Learning from Pixels?
Xiang Li, Jinghuan Shang, Srijan Das, and Michael S. Ryoo
Neural Neural Textures Make Sim2Real Consistent
, Jinghuan Shang, Xiang Li, and Michael S. Ryoo
[Project Page] [Code] [arXiv]
StARformer: Transformer with State-Action-Reward Representations for Robot Learning
Jinghuan Shang, Xiang Li, Kumara Kahatapitiya, Yu-Cheol Lee, Michael S. Ryoo
IEEE TPAMI, Special Issue on Transformer Models in Vision, 2022
[PDF] [IEEE Xplore] [Code]
StARformer: Transformer with State-Action-Reward Representations for Visual Reinforcement Learning
Jinghuan Shang, Kumara Kahatapitiya, Xiang Li, and Michael S. Ryoo
[arXiv] [Code] [Video] [Poster]
Self-Supervised Disentangled Representation Learning for Third-Person Imitation Learning
Jinghuan Shang and Michael S. Ryoo
[arXiv] [Talk] [Digest Slide]
|2022/10||- NeurIPS 2022 Scholar Award|
|2018/08||- Merit Scholarship from the Department of Computer Science at Stony Brook University|
|2018/06||- Outstanding graduate among all graduates from universities in Shanghai|
|2016||- 1st Prize in Shanghai Division of China Undergraduate Mathematical Contest in Modeling (CUMCM)|
|2015-2017||- 3 times of Academic Excellence Scholarship at Shanghai Jiao Tong University|
I love cooking.
I solve some algorithm problems in my spare time. Luckily got Top 10 in 2020 SBU ICPC Slection Contest. Here is my [Leetcode].
Last modified 2022/09. Style Credit: latex.css