Summary
Yuan Huang is a senior research scientist and machine learning engineer with 11 years of experience applying statistical modeling, Monte Carlo simulation, and modern deep learning to real-world products and scientific discovery. After earning dual PhDs in Quantum Information and Condensed Matter Physics, he translated rigorous quantitative research into production ML—driving recommendation, ranking, and generative audio efforts at Meta and now accelerating science with AI at DP Technology. His toolkit spans Bayesian hierarchical models to CNNs/RNNs and social-network analysis, informed by a strong background in unbiased Monte Carlo methods developed during his academic career. Comfortable moving between research and engineering, he has led applied ML teams, built end-to-end recommendation systems, and delivered production services at scale across e-commerce and social platforms. A less obvious strength is his track record of finding novel phase transitions in complex physical models, reflecting a knack for uncovering subtle signal in noisy, high-dimensional data.
11 years of coding experience
8 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Quantum Infomation Physics, Doctor of Philosophy (Ph.D.) Quantum Infomation Physics at University of Science and Technology of China
Doctor of Philosophy - PhD Physics, Doctor of Philosophy - PhD Physics at University of Massachusetts Amherst
English, Chinese