Dr. Zheqing (Bill) Zhu is the Founder and CEO of Pokee AI and former head of Applied Reinforcement Learning team at Meta AI. Bill leads Pokee AI to build the next-generation foundation AI agents that excel in reasoning, planning and tool usage. Pokee AI’s foundation tool usage model surpasses GPT4o, Claude 3.7 and Gemini 2.5 pro in function calling by a large margin and can easily extend to more than 6000 tools. So far, Pokee AI has secured 12M USD seed round funding from Point72 Ventures, with participation from Qualcomm Ventures, Samsung NEXT, among others as well as top angels such as Lip-bu Tan (CEO of Intel) and Ahbay Parasnis (Founder of Typeface and ex-CTO of Adobe).

Before Pokee AI, Bill was a Senior Staff Research Lead Manager at Meta AI, where he served as the Head of Applied Reinforcement Learning team. He led the development and open-sourcing of Pearl, Meta’s flag-ship reinforcement learning training platform for production use cases and deployed RL models across ads, recommender systems, and reality labs, realizing more than 500M USD of annual revenue. Prior to this position, he served as a Engineering Manager and a technical lead for Meta’s Ads Growth Machine Learning team, where he built the first advertiser growth AI product and grew Meta’s active advertisers from 2M to 12M.

Bill earned his PhD degree in Reinforcement Learning at Stanford University, advised by Professor Benjamin Van Roy, while working full-time at Meta AI leading the Applied Reinforcement Learning team. His main research focus is to understand theoretical and practical gaps in existing reinforcement learning algorithms in a real-world context. He received Master of Science in Computer Science from Stanford University (also while full-time at Meta AI) and Bachelor of Science in Computer Science with a Minor in Finance, summa cum laude, from Duke University. He has been the recipient of the Asian American Science and Engineering Innovation Award from CIE/SEA, the Alex Vasilos Memorial Award, the Highest Distinction Graduate Award from Duke University and Ericsson BUSS Shanghai Quarterly Technical Award. His publications have appeared in top venues including JMLR, ICML, ICLR, KDD, Machine Learning, RecSys, ICRA, IROS and more.