Che Wang

Postdoc, Amazon

Joined

September 2019

Names

Che Wang (Preferred)

Emails

****@nyu.edu (Confirmed)

Personal Links

Career & Education History

Postdoc

Amazon (amazon.com)

2023 – Present

PhD student

New York University (nyu.edu)

2017 – 2023

Undergrad student

New York University (nyu.edu)

2013 – 2017

Advisors, Relations & Conflicts

PhD Advisor

2017 – 2022

Expertise

machine learning

,

deep learning

,

reinforcement learning

2016 – Present

Publications

GAM: Generalized Action Model for Robotic Manipulation
Uday Kamal, Jeffrey Jiang, Chaitanya Mitash, Weiyao Wang, Ikechukwu Obi-Okoye, Che Wang, Aatif Jiwani, Huitan Mao, Hai Huu Nguyen, Michel Breyer, Wenyu Xia, Nikhil Mishra, Kostas Bekris, Kapil Katyal
- ICRA 2026: From Data to Decisions Poster
- Readers: Everyone
Pre-training with Synthetic Data Helps Offline Reinforcement Learning
Zecheng Wang, Che Wang, Zixuan Dong, Keith W. Ross
- ICLR 2024 poster
- Readers: Everyone
Aggressive Q-Learning with Ensembles: Achieving Both High Sample Efficiency and High Asymptotic Performance
Yanqiu Wu, Xinyue Chen, Che Wang, Yiming Zhang, Keith W. Ross
- 08 Oct 2022 (modified: 08 Feb 2026)
- Deep RL Workshop 2022
- Readers: Everyone
Reinforcement Learning with Automated Auxiliary Loss Search
Tairan He, Yuge Zhang, Kan Ren, Minghuan Liu, Che Wang, Weinan Zhang, Yuqing Yang, Dongsheng Li
- Published: 31 Oct 2022, Last Modified: 08 Feb 2026
- NeurIPS 2022 Accept
- Readers: Everyone
VRL3: A Data-Driven Framework for Visual Deep Reinforcement Learning
Che Wang, Xufang Luo, Keith W. Ross, Dongsheng Li
- Published: 31 Oct 2022, Last Modified: 08 Feb 2026
- NeurIPS 2022 Accept
- Readers: Everyone
On the Convergence of Monte Carlo UCB for Random-Length Episodic MDPs
Zixuan Dong, Che Wang, Keith W. Ross
- 2022 (modified: 05 Oct 2022)
- CoRR 2022
- Readers: Everyone
VRL3: A Data-Driven Framework for Visual Deep Reinforcement Learning
Che Wang, Xufang Luo, Keith W. Ross, Dongsheng Li
- 2022 (modified: 05 Oct 2022)
- CoRR 2022
- Readers: Everyone
On the Convergence of the Monte Carlo Exploring Starts Algorithm for Reinforcement Learning
Che Wang, Shuhan Yuan, Kai Shao, Keith W. Ross
- 2022 (modified: 05 Oct 2022)
- ICLR 2022
- Readers: Everyone
Reinforcement Learning with Automated Auxiliary Loss Search
Tairan He, Yuge Zhang, Kan Ren, Minghuan Liu, Che Wang, Weinan Zhang, Yuqing Yang, Dongsheng Li
- 2022 (modified: 16 Nov 2022)
- CoRR 2022
- Readers: Everyone
AARL: Automated Auxiliary Loss for Reinforcement Learning
Tairan He, Yuge Zhang, Kan Ren, Che Wang, Weinan Zhang, Dongsheng Li, Yuqing Yang
- Published: 28 Jan 2022, Last Modified: 13 Feb 2023
- ICLR 2022 Submitted
- Readers: Everyone

View all 23 publications

Co-Authors

View all 38 co-authors