Zheqing (Bill) is the engineering manager for the Applied Reinforcement Learning group within Meta AI. The Applied Reinforcement Learning group aims to bring the state-of-the-art reinforcement learning technology to life by pushing the frontier of industry-ready reinforcement learning technologies. The team owns Meta's reinforcement learning stack and spans across dozens of product reinforcement learning usecases. Our application and research areas include but are not limited to recommender system, user contextual understanding, control mechanisms, and many more. The team also developed and currently owns Meta's open source reinforcement learning platform ReAgent (reagent.ai).
Bill's personal research interest lies in bridging the gap between theoretical reinforcement learning with practical applications. Some of the reinforcement learning topics that Bill is particularly interested in are improving sample complexity, handling nonstationarity, generalization of value functions, and representation of agent-environment history.
January 06, 2024
Geng Ji, Wentao Jiang, Jiang Li, Fahmid Morshed Fahid, Zhengxing Chen, Yinghua Li, Jun Xiao, Chongxi Bao, Zheqing (Bill) Zhu
January 06, 2024
September 12, 2023
Bill Zhu, Alex Nikulkov, Dmytro Korenkevych, Fan Liu, Jalaj Bhandari, Ruiyang Xu, Urun Dogan
September 12, 2023
September 12, 2023
Bill Zhu, Benjamin Van Roy
September 12, 2023
September 06, 2023
Bill Zhu, Benjamin Van Roy
September 06, 2023
June 15, 2023
Yingchen Xu, Bobak Hashemi, Lucas Lehnert, Rohan Chitnis, Urun Dogan, Zheqing (Bill) Zhu, Olivier Delalleau
June 15, 2023
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