I’m a PhD student at OSI Lab and OptiML Lab in the Kim Jaechul Graduate School of AI at KAIST, where I am very fortunate to be jointly advised by Se-Young Yun and Chulhee Yun. I completed my MSc in the same school (thesis: Near-Optimal Clustering in Block Markov Decision Processes) and my BSc in Mathematical Sciences and Computer Science (double major, cum laude), also at KAIST.

In broad terms, my interest lies in mathematical and theoretical AI. I’ve been recently focused on statistical problems arising from RLHF, divided into two parts. One is tackling related interactive machine learning problems, such as sequential decision-making (bandits, online learning), reinforcement learning (MDPs), active learning, and more. Another is obtaining tight statistical guarantees for identifying and exploiting underlying low-dimensional structures in RLHF problems. In addition, I enjoy exploring fundamental concepts in statistics and probability theory, such as Markov chains, concentration inequalities, general questions in learning theory, and more. My other, albeit still significant, research interests encompass algorithmic fairness, deep learning theory from both optimization and statistical perspectives, and essentially any machine learning challenges necessitating mathematical analysis. (See here for a third-person bio.)

Feel free to reach out if you are interested in collaborating in any of the aforementioned topics, and/or if you have any questions in any of my work, and/or you just want to chat in general!

I also play the violin occasionally. I was a first violinist at the KAIST Orchestra (KAO), MDOP Orchestra at Kyung Hee University, Merry Orchestra, and recently, KAO-S.

(Late update: 2024.09.27)