Kwei-herng Lai is an applied scientist and PhD candidate in computer science with around a decade of experience building production-ready machine learning systems across anomaly detection, recommendation, graph representation learning, and reinforcement learning. He has partnered with industry leaders—Microsoft, Apple, General Motors, Visa, Trane, KKBOX and Cathay United Bank—translating research into scalable solutions that improved stability and business performance. His work spans both academic venues (IJCAI, AAAI, KDD) and high-impact engineering: open-source projects for imperfect-information game AI (600+ stars) and large-scale network representation learning (200+ stars). At Texas A&M and Rice he developed unsupervised fault detection and game-AI toolkits, and at Visa explored domain adaptation for time-series anomaly detection to enable cross-domain transfer. Currently at Microsoft after a stint as a machine learning engineer at Apple, he blends deep research rigor with hands-on productization experience in San Diego. A less obvious strength is his consistent track record of turning complex academic models into practical, production-grade pipelines used in diverse industrial settings.
10 years of coding experience
8 years of employment as a software developer
Bachelor of Science (B.S.) Computer Science, Bachelor of Science (B.S.) Computer Science at National Chengchi University
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Rice University
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Texas A&M University
Contributions:3 releases, 4 commits, 3 pushes in 5 years 8 months
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.