Hua Zheng is a Senior Research Scientist at Meta with a decade of experience building large-scale analytics, search, and recommender systems informed by rigorous academic training (PhD in Engineering) and an MS in Statistics. His work bridges deep reinforcement learning, stochastic optimization, physics-informed deep learning, and graphical models, with hands-on production experience in distributed systems like Spark, Solr, and AWS. He has led cross-disciplinary projects from a Pfizer-collaborative digital-twin platform to cold-start forecasting libraries at AWS, demonstrating an ability to translate cutting-edge research into deployable ML solutions. Comfortable moving between theory and engineering, he also supervised PhD students and contributed novel modeling (e.g., Bayesian causal recommendation) while operationalizing large streaming pipelines processing billions of events. Based in Sunnyvale, Hua blends mathematical depth with pragmatic system design, often applying physics-inspired priors to accelerate learning in real-world ML tasks.
10 years of coding experience
9 years of employment as a software developer
Master of Science (MS), Statistics, Master of Science (MS), Statistics at University of Washington
Doctor of Philosophy - PhD, Engineering, Doctor of Philosophy - PhD, Engineering at Northeastern University
Bachelor of Science (BS), Mathematics, Bachelor of Science (BS), Mathematics at Shandong University
The potential for the use of AI is dramatic especially as it can assist family clinicians who are usually overloaded with patients to make better choices for treatment of their type 2 patients in order to help prevent hyperglycemia, hypertension and CV risk outcomes.
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