Summary
Zihan Wang is an AI researcher and entrepreneur with nine years of experience building foundation models and core learning algorithms across LLMs, VLMs, imitation learning, reinforcement learning, and meta-learning. He has collaborated with leading figures in the field and published at NeurIPS, ICML, ICLR, CoRL, and ICRA, blending rigorous academic work (PhD candidate at Paul G. Allen School / MSCS at Stanford) with hands-on product R&D. Zihan has co-founded two startups and led AI efforts in healthcare and robotics, translating research into real-world systems and commercial products. His recent industry roles include research scientist positions at Scale AI and an AI researcher appointment at Meta, demonstrating a trajectory from academic labs to high-impact industry teams. Notably, he combines deep theoretical expertise with practical system-building—having shipped research-driven engineering during internships and early-career roles at organizations like TuSimple and SAIL. Based in Palo Alto, he focuses on leveraging foundation models and embodied agents to tackle complex, real-world challenges.
9 years of coding experience
7 years of employment as a software developer
Bachelor of Applied Science (B.A.Sc.) Engineering Science (Robotics Option), Bachelor of Applied Science (B.A.Sc.) Engineering Science (Robotics Option) at University of Toronto
Master's degree Computer Science, Master's degree Computer Science at Stanford University
English, Chinese