Summary
Zhengfeng Lai is a senior research scientist and tech lead specializing in world models, multimodal and video large language models, and data-centric approaches to image/video generation with nine years of research and industry experience. He has led VLM training efforts from compact architectures to extremely large Mixture-of-Experts models and co-developed open-source world models, including the PAN world simulation release. At Apple and MBZUAI he drove video foundation-model research and practical systems for long-horizon, token-efficient video understanding and streaming video assistants, and his work spans few-shot, semi-supervised and unsupervised domain adaptation methods. His background includes applied roles at Amazon Lab126 and entrepreneurial leadership in medical-device ML, where he translated user research into a neonatal screening product. He holds a PhD from UC Davis and has EB-1A approval, reflecting recognized impact in AI research. Based in Cupertino, he combines deep academic rigor with product-minded engineering and a persistent focus on label- and data-efficiency in real-world multimodal systems.
9 years of coding experience
6 years of employment as a software developer
Doctor of Philosophy - PhD, Electrical and Computer Engineering, Doctor of Philosophy - PhD, Electrical and Computer Engineering at University of California, Davis
Bay-Area Regional Innovation CORPS Training, Bay-Area Regional Innovation CORPS Training at University of California, Berkeley, Haas School of Business
Bachelor of Engineering - BE, Information Engineering, Bachelor of Engineering - BE, Information Engineering at Zhejiang University