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), also at KAIST. During my undergraduate years, I participated in research with four different groups covering a range of fields (refer to ‘Experiences’). Since then, I have been also working closely with Chang D. Yoo and Gwangsu Kim.

In broad terms, my interest lies in mathematical and theoretical AI, which I consider crucial for ensuring the solidity of our current achievements and guiding future developments. I’ve been recently focusing on obtaining tight statistical guarantees (regret, sample complexity, etc.) for interactive machine learning, such as sequential decision-making (bandits, online learning), reinforcement learning (MDPs), active learning, and more. In addition, I enjoy exploring fundamental concepts in statistics and probability theory, such as Markov chains, concentration inequalities, general questions in learning theory, and most recently, safe anytime-valid inference (SAVI). 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.

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.