I am on the 2026–2027 academic job market. My CV is available here.

Upcoming talk at the 2026 INFORMS Annual Meeting, San Francisco
"Designing First-Order Methods with Provable Guarantees via a Data-Driven Approach"
Session: Data-Driven Optimization and Decision Calibration
Nov 1, 11:00AM–12:15PM, South 206

I am a postdoctoral research associate at the Department of Operations Research and Financial Engineering at Princeton University, working with Prof. Bartolomeo Stellato.

My research interest lies in mathematical optimization and theoretical aspects of machine learning. My recent work focuses on data-driven analysis and design of first-order methods, providing performance guarantees for optimization algorithms via distributionally robust optimization and exact verification. I am also working on accelerating general-purpose first-order solvers.

I obtained Ph.D. from the Department of Mathematical Sciences at Seoul National University (SNU), where I studied classical fixed-point iterations from both theoretical and practical perspectives. My advisor was Prof. Ernest K. Ryu.