Summary
Nathan Yu is a machine learning engineer with nine years of experience applying probabilistic ML, optimization, and generative modeling to large-scale recommendation and advertising systems. Currently at TikTok, he focuses on live strategy recommendation, and previously led recommendation algorithm work for Tencent’s online advertising using deep learning, representation learning, multi-task models, causal inference, and sequence modeling. He holds a PhD in Computer Science from the National University of Singapore and has research roots as a postdoc and RA, giving him a strong bridge between principled research and production engineering. Nathan’s background spans academic rigor and industry impact—he’s equally comfortable designing approximate inference methods as deploying real-time recommendation strategies. Based in Canada, he combines a multidisciplinary education (including exchange at MIT and a BEng in Mechanical Engineering) with hands-on experience in OCR and face recognition from earlier roles. Colleagues describe him as pragmatic and resilient—aptly summarized by his terse GitHub bio, “Surviving.”
9 years of coding experience
6 years of employment as a software developer
Business Administration and Management, General, A, Business Administration and Management, General, A at National Cheng Kung University
Doctor of Philosophy (PhD), Computer Science, Doctor of Philosophy (PhD), Computer Science at National University of Singapore
Exchange Student, Computer Science, Exchange Student, Computer Science at Massachusetts Institute of Technology
Diploma, Diploma at The Affiliated High School of Jilin University
Bachelor of Engineering (BEng), Mechanical Engineering and Automation, 3.83/4, Bachelor of Engineering (BEng), Mechanical Engineering and Automation, 3.83/4 at Beihang University
Chinese, English, Japanese