Summary
Yifang Chen is a research-driven machine learning scientist and Member of Technical Staff at Microsoft AI with a decade of experience focused on online learning, bandits (multi-armed and contextual), optimization, and reinforcement learning. Currently completing a PhD in Computer Science at the University of Washington, she blends theoretical rigor—seeking provable guarantees—with practical ML deployments from internships at Google, Meta, Baidu, and Microsoft Research. Her work spans active learning, representation learning, and novel applications such as RL for LLM reasoning and online algorithms for quantum computing, reflecting a knack for applying theory to emerging domains. Notably, she has built configurable PyTorch tooling for exploratory transforms and developed integrity-focused active learning methods with weak labelers, showing both systems and algorithmic fluency. Based in Los Angeles, Yifang pairs strong academic mentorship and cross-industry research to drive robust, provably sound learning algorithms.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD Computer science, Doctor of Philosophy - PhD Computer science at University of Washington
Master's degree Electrical and Electronics Engineering, Master's degree Electrical and Electronics Engineering at University of Southern California
German, English, Chinese