Talks
Invited talks, tutorials, and research presentations. For lab reading groups and seminar materials, see Lab Seminars.
2026
Provably Efficient Regularized Online RLHF with Generalized Bilinear Preferences
Invited Talk at Chung-Ang University, Seoul, Republic of Korea
Host: Prof. Kyoungseok Jang
2025
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Top Conference Session (KSC 2025), Yeosu EXPO Convention Center, Yeosu, Republic of Korea
Bandits 101
Invited Seminar at IIDS Lab, KAIST, Daejeon, Republic of Korea
A Primer on Bandits and Two Recent Theoretical Advances in Generalized Linear Bandits
Invited Talk at Department of Statistics, Jeonbuk National University, Jeonju, Republic of Korea
Host: Prof. Gwangsu Kim
Two Theoretical Advances on Sample-Efficient Preference Learning
Reading Group at UCL, online
Hosts: Prof. Ilija Bogunovic & Dr. Sangwoong Yoon
2024
Bandits 101 @Hyperconnect: A Maximally Non-technical Tutorial
Invited Talk at Hyperconnect, Asem Tower, Seoul, Republic of Korea
Host: Dr. Gihun Lee
A Unified Confidence Sequence for Generalized Linear Models, with Applications to Bandits
Invited Session: Bandit and Reinforcement Learning Theory (CKAIA 2024), BEXCO, Busan, Republic of Korea
Host: Prof. Min-hwan Oh
On Various Statistical Problems Arising from Preference Learning and RLHF + Misc. Theories
SNU-KAIST AI/ML Theory Workshop, St. John's Hotel, Gangneung, Republic of Korea
Nearly Optimal Latent State Decoding in Block MDPs
Learning in Networks: Structure, Dynamics, and Control (part of Digital Futures Focus Period Program), KTH, Stockholm, Sweden
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion, and Beyond
DeLTA Seminar, University of Copenhagen, Copenhagen, Denmark
Nearly Optimal Latent State Decoding in Block MDPs
Junior Researcher Session, Summer School on Optimal Transport, Stochastic Analysis, and Application to Machine Learning, Daejeon, Republic of Korea
Bandits 101 + Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
Invited Talk at ITML Lab, Yonsei University, Seoul, Republic of Korea
Host: Prof. Jy-Yong Sohn
Improved Regret Bounds of (Multinomial) Logistic Bandits via Regret-to-Confidence-Set Conversion
“Mini RL Theory Workshop”, Universitat Pompeu Fabra, Barcelona, Spain
Host: Prof. Gergely Neu
2023
Fair Streaming Principal Component Analysis: Statistical and Algorithmic Viewpoint
Top Conference Session (KSC 2023), Busan, Republic of Korea
Nearly Optimal Latent State Decoding in Block MDPs
Invited Session on “Stochastic learning in structured systems”, 21st INFORMS Applied Probability Society (APS) Conference, Nancy, France
Host: Prof. Jaron Sanders
Nearly Optimal Latent State Decoding in Block MDPs
Top Conference Session (KCC 2023), Jeju Island, Republic of Korea
2022
Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold
Top Conference Session (KSC 2022), Jeju Island, Republic of Korea
Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold
KAIST Math Graduate Student Seminar (KMGS), online
Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold
KAIST Math, online
Host: Prof. Donghwan Kim
2021
Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold
KAIST EE - ICL CS Joint Seminar, online
Hosts: Prof. Chang D. Yoo & Prof. Yingzhen Li
Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold
KAIST EE - ICL CS Joint Seminar, online
Hosts: Prof. Chang D. Yoo & Prof. Björn Schuller
Fast and Efficient MMD-based Fair PCA via Optimization over Stiefel Manifold
UIUC ECE 590SIP Seminar, online