I am currently an assistant professor in the Department of Statistics at Korea University, Seoul. Prior to this, I served as an assistant professor in the Department of Artificial Intelligence at Chung-Ang University (2021–2024). Before then, I earned my B.S. in Electrical Engineering and Computer Science from Seoul National University in 2015, followed by a Ph.D. in Electrical and Computer Engineering from the same university in 2021 under the supervision of Prof. Songhwai Oh.

• Black-Box Optimization 

  • Bandit Algorithms: Heavy-tailed bandits, Minimax optimal heavy-tailed bandits

  • Bayesian Optimization: Heavy-tailed BO

  • Combinatorial Optimization: Perturbation-based exploration for MCTS, Learning-based boosting

• Reinforcement Learning and Its Variants

  • Regularized Markov Decision Processes: Maximum Tsallis entropy RL (and its special case)

  • Preference-Based Reinforcement Learning (RL from Human Feedback): Sequential comparison for efficient PbRL

  • Safe Reinforcement Learning: Gradient aggregation for multiple constraints, Spectral risk safe RL

  • Distributional Reinforcement Learning: Pertrubed exploration for dist. RL, Eluder dimension-based regret analysis for dist. RL

• Imitation Learning

  • Inverse Reinforcement Learning: IRL with negative demonstrations

  • Generative Adversarial Imitation Learning: Maximum Tsallis entropy framework

• Smart Assembler: Robot Active Learning for Unseen Parts Assembly

  • Funded by NRF [우수신진연구, 최초혁신실험실]

• Development of Emotion Recognition/Generation-based Interacting Edge Device Technology for Mental Health Care

  • Funded by IITP

• Development of Stock Prediction Models using Explainable AI with Multi-modal Data and Deep Reinforcement Learning

  • Funded by NRF

• Development of a lightweight gripper and an object recognition system

  • Funded by Seoul Business Agency

• Development of AI Algorithm for Operator Assistance

  • Funded by Doo-San

• Development of Reinforcement Learning Algorithm for Urban Autonomous Driving

  • Funded by Hyundai NGV

• CAN Data-based Forklift CUP Analysis

  • Funded by Doo-San

• Uncertainty Aware Task and Motion Planning

  • Funded by NRF

• Reinforcement Learning based Press Molding Optimization

  • In collaboration with Hyundai NGV

• Domain Generalization with Pre-trained Models

  • In collaboration with Kakao Brain

  • This work was published at ECCV 2022

• Developing Embedded AI Systems

  • Funded by Doo-San

• Domain Generalization via Finding Flat Minima

  • In collaboration with Naver Clova AI 

  • This work was published at NeurIPS 2021

• Tsallis Entropy Reinforcement Learning

  • In collaboration with Kakao Brain 

  • This work was published at RSS 2020