Dr. Wei Chu

Dr. Wei Chu is Chief Scientist and Co-Founder of INF, where he leads the company’s scientific direction and the development of large language model solutions purpose-built for real-world, industry-grade deployment. A seasoned R&D leader and award-winning researcher, he brings over two decades of experience spanning academia and industry, with a career defined by translating frontier machine learning research into scalable, production-ready systems. Prior to founding INF, Dr. Chu was Senior Director of Engineering at Ant Group, where he led the cognitive computing department, overseeing large teams building AI platforms across natural language understanding, computer vision, and knowledge graphs. Earlier, he served as Director of Engineering at Alibaba Cloud, heading PAI 2.0, the company’s distributed machine learning platform, and held senior applied science roles at Microsoft Bing and Yahoo! Labs, where his work on personalized search and web-scale content optimization later received multiple Test of Time awards.

Dr. Chu’s academic foundations are equally distinguished. He completed three years of postdoctoral research at the Gatsby Computational Neuroscience Unit at University College London under the mentorship of Professor Zoubin Ghahramani, followed by applied research at Columbia University. He earned his Ph.D. from the National University of Singapore under the joint supervision of Professors S. Sathiya Keerthi and Chong Jin Ong, grounding his work in rigorous statistical machine learning and real-world application.

Widely published across top-tier conferences and journals, Dr. Chu’s research has been cited more than 10,000 times. His work focuses on building equitable, trustworthy, and interpretable AI systems, with recent contributions spanning industry-focused LLMs and practical frameworks for deploying AI safely and effectively at scale. A recipient of multiple best paper, best demo, and test-of-time awards, his career reflects sustained impact at the intersection of research excellence, infrastructure, and real-world AI adoption.