Yang Song
VP Of Recommendation Research
United States
Summary
👤
Senior🎓
Top SchoolYang Song is a seasoned research and engineering leader specializing in recommendation systems, search, and large-scale machine learning, currently VP of Recommendation Research at Meta. He combines a PhD-backed research pedigree and over a decade of product impact—shipped deep-learning QA features for Bing, Cortana ranking, and a demographics inference pipeline serving over a billion users—with hands-on systems programming in C++, Java, C#, and Python. Yang has led massive teams (100–400+ engineers and researchers) at TikTok, Kuaishou, and Google to optimize engagement and growth metrics across global short-video, e-commerce, and search products. A prolific academic, he has published 50+ papers in top venues while translating research into production at scale, including Microsoft Academic Search and Bing index metrics. Notably, he blends blue-chip industry leadership with a developer’s mindset—self-described “A Data Player!”—and a track record of defining company-level metrics that moved market share.
10 years of coding experience
15 years of employment as a software developer
PhD Computer Science and Engineering, PhD Computer Science and Engineering at Penn State UniversityB.S Computer Science and Engineering, B.S Computer Science and Engineering at Zhejiang UniversityGithub contributions (5)
AbnerYang/Top-solutions-of-Data-Mining-Competitions
Mar 2018 - Mar 2018
Contributions:86 commits, 84 pushes, 1 branch in 1 day
AbnerYang/Natural-Language-Inference
Oct 2018 - Oct 2018
Contributions:32 commits, 30 pushes, 1 branch in 8 days
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