Hello, my name is Jaeyeon Kim! I’m a first-year Ph.D. student at Harvard CS, prospectively advised by Sitan Chen and Sham Kakade.

My academic journey began in junior high school, with multiple awards in Math Olympiads. Since then, I’ve been driven by a passion for solving challenging problems through mathematics. Afterward, I earned a B.S. in Mathematics from Seoul National University, where I enjoyed organizing mathematical concepts in my own words.

During my undergraduate years, I had the privilege of working with Prof. Ernest Ryu in Optimization Theory-leading to the discovery of H-duality-a duality between first-order algorithms. Unlike conventional dualities, H-duality characterizes the relationship between algorithms themselves. My research has since extended to various setups. (Mirror Descent, Fixed-point problems).

At Harvard, my research has shifted toward Diffusion Models. With incredible advisors, my recent work on Masked Diffusion Models sheds light on their training and inference processes. My broader goal is to develop efficient generative models for discrete data while deepening our mathematical understanding of Diffusion Models.

I’m always happy to chat about Machine Learning, Optimization, and beyond—feel free to reach out!