Yongyang Yu is a Staff Research Scientist with 12 years of experience building large-scale data and privacy infrastructure at Meta, combining deep expertise in data mining, numerical computing, and production ML systems. He has led cross-functional programs to automate ownership discovery, metric optimization, and privacy-compliant demographic inference, shipping multiple prediction methods and tooling into production. Comfortable across Java, C/C++, Python, Scala and more, he bridges research and engineering—designing gradient-boosted models, query optimizers, and distributed matrix extensions for high-performance analytics. His work includes practical instrumentation such as web crawlers for metadata collection and reaper bots that eliminated significant metric redundancy. Trained as a Ph.D. computer scientist at Purdue, he pairs rigorous numerical methods research with hands-on systems design and developer tooling. Based in Sunnyvale, he quietly excels at turning complex algebraic and privacy constraints into robust, scalable pipelines that ship.
12 years of coding experience
15 years of employment as a software developer
Doctor of Philosophy (Ph.D.), Computer Science, Doctor of Philosophy (Ph.D.), Computer Science at Purdue University
Master of Engineering (M.Eng.), Computer Science and Technology, Master of Engineering (M.Eng.), Computer Science and Technology at Harbin Institute of Technology
Contributions:33 pushes, 2 branches in 5 years 9 months
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