I’m a PhD candidate in Applied & Computational Mathematics at Caltech. I feel very fortunate to be working with Professor Franca Hoffmann on mean-field theory, interacting particle systems, and collective dynamics. We began collaborating in May 2023. Earlier, until the end of 2022, I was advised by Professor Oscar Bruno on high-performance numerical methods for PDE, which shaped my appreciation for both analytical structure and computational performance.

My current research lies at the intersection of interacting particle systems, mean-field limits, and stochastic optimization and sampling algorithms such as Consensus-Based Optimization/Sampling (CBO/S). I’m particularly interested in understanding how macroscopic behaviors emerge from microscopic dynamics, and how tools from kinetic theory, probability, and partial differential equations can be used to rigorously analyze and design efficient algorithms.

For details, please visit Research tab! Feel free to contact me if you are interested in discussing more about those topics :) 

Prior to joining Caltech, I received a BBA in Business Management and a BS in Mathematics Summa Cum Laude from Yonsei University, where I was also the valedictorian. I began in business, but after taking my first math class in junior year, I found myself wanting to learn more. I ended up adding a second major and took advanced courses in real analysis, PDEs, topology, abstract algebra, and more—initially mainly out of curiosity, but later leading me to change fields in my last semester in college and pursue mathematics in graduate school.

For details, please visit Others or CV tab!