Xiaocheng Tang is an AI research scientist and engineering manager with 13 years of experience building large-scale ML, RL, and optimization systems for recommendation, ride-hailing marketplaces, and autonomous driving. He has led RL-based decision-making and motion planning R&D at DiDi and currently works on LLMs, RLHF, and advanced ranking models for Instagram Reels at Meta. Xiaocheng holds a PhD in Optimization and Machine Learning and has 30+ top-conference publications, patents, and journal articles, including work published in Mathematical Programming and award-winning contributions at NeurIPS and ICLR. He combines deep theoretical expertise in scalable training and convergence theory with production engineering—an Apache MADlib committer and former contributor to large-scale systems at Pivotal, Yahoo, and IBM. Notably, his RL solutions have won NeurIPS Best Demo and an INFORMS operations research prize, and his motion-prediction models ranked top on the Waymo Open Dataset challenge. Based in California, he blends rigorous optimization research with hands-on deployment experience across industry-scale ML products.
13 years of coding experience
14 years of employment as a software developer
Ph.D, Optimization and Machine Learning, Ph.D, Optimization and Machine Learning at Lehigh University
Bachelor of Engineering, Chu Kochen Honors College, Bachelor of Engineering, Chu Kochen Honors College at Zhejiang University
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