In this session, Zheqing (Bill) Zhu, Founder and CEO of Pokee AI, will share how the company is pioneering a new era in general AI agents and workflow automation. Drawing on his extensive background in leading the applied reinforcement learning team at Meta AI and his Stanford PhD, Bill will explain how Pokee AI’s technology transcends conventional AI by using RL‑based planners that enable interactive, personalized, and tool‑savvy AI agents. Attendees will learn how these agents achieve over 97% accuracy in navigating and integrating with thousands of tools, and how a recent US$12 million seed round led by Point72 Ventures will accelerate the company’s mission to make digital automation truly effortless and scalable.
Introduction – Zheqing (Bill) Zhu, Founder & CEO, Pokee AI
Zheqing (Bill) Zhu is the Founder and CEO of Pokee AI and former head of Applied Reinforcement Learning team at Meta AI. Pokee AI is a general AI agent company that scales to thousands of tools across the internet, which has raised a US$12 million seed round, led by Point72 Ventures with important contributions from Qualcomm Ventures, Samsung NEXT, among others, and high‑profile angels including Lip‑bu Tan (CEO of Intel) and Abhay Parasnis (former CTO of Adobe).
Before founding Pokee AI, Bill led the Applied Reinforcement Learning group at Meta AI. He played a central role in developing Meta’s flagship open‑source RL platform Pearl, published in JMLR, and drove transformative business value by generating over $500 million in annual revenue and scaling monthly active advertisers from 2 million to 12 million
Bill completed his PhD in Reinforcement Learning at Stanford University under Professor Benjamin Van Roy, all while spearheading Meta’s Applied RL team full-time. His research has been featured in top-tier conferences and journals including JMLR, ICML, ICLR, KDD, RecSys and many more.
On-Campus Recruitment Talk
Date: Friday, 29 August 2025
Time: 3pm – 4.30pm
Event Venue: FASS AS7 Seminar B (Level 1)
Industry: Information Communications Technology
Faculties: All Faculty/ Schools, Faculty of Arts & Social Sciences, Faculty of Engineering, Faculty of Science, School of Business, School of Computing
Target Audience: All UG and PG (Masters & PhD)
Dress Code: Smart Casual
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