Shifan Mao is a software engineer in Palo Alto with 11 years of experience building ML-driven personalization and search systems at Google and YouTube. He has advanced from research-focused roles in search ranking to pioneering deep learning models for feed recommendation and exploring LLMs as video recommenders. His background blends a Ph.D. in Chemical Engineering from Stanford and a double bachelor’s in Mathematics and Chemical Engineering with hands-on data mining work on three decades of fusion experiment data. That interdisciplinary foundation informs a pragmatic approach to modeling complex user behavior and scaling production systems. Based in Silicon Valley, he brings both research rigor and product-focused engineering to problems at the intersection of recommender systems, large models, and user satisfaction. Notably, his trajectory shows a rare shift from scientific experimental analysis to leading-edge personalization research within flagship consumer products.
11 years of coding experience
9 years of employment as a software developer
Chemical Engineering, Chemical Engineering at Universidad de Oviedo
Bachelor's Degree Double major in Mathematics Chemical Engineering, Bachelor's Degree Double major in Mathematics Chemical Engineering at University of Wisconsin-Madison
Doctor of Philosophy (Ph.D.) Chemical Engineering, Doctor of Philosophy (Ph.D.) Chemical Engineering at Stanford University
Chinese, English, Spanish, Japanese, Chinese, French
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