Yi Mao is a researcher in Mountain View with nine years of experience building and evaluating intelligent systems across Microsoft and Google, specializing in natural language generation, QA over structured data, and deep reinforcement learning. With a Ph.D. in Computational Science and an MSECE, Yi has a strong foundation in both theory and applied relevance tuning—from personalized and local search to app recommendation systems. At Microsoft they have moved from applied relevance roles into research-focused NLG and RL work, bridging product-driven evaluation with cutting-edge model development. Known for improving search and recommendation relevance in production settings, Yi combines rigorous experimentation with pragmatic deployment insights.
9 years of coding experience
6 years of employment as a software developer
MSECE, Electrical and Computer Engineering, MSECE, Electrical and Computer Engineering at Purdue University
Doctor of Philosophy (Ph.D.), Computational Science and Engineering, Doctor of Philosophy (Ph.D.), Computational Science and Engineering at Georgia Tech
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