Yongjae Shin

I am a Ph.D. student at Smart Information Systems Research Lab (SISReL) in Korea Advanced Institute of Science and Technology (KAIST) advised by Professor Youngchul Sung.

News

Jan 2026	Two papers (FINO, FAC) accepted to ICLR 2026.
May 2025	Two papers (OPT, PARS) accepted to ICML 2025.
Mar 2024	Started an internship at LG AI Research.
Sep 2023	RDE paper accepted to NeurIPS 2023.

Flow Matching with Injected Noise for Offline-to-Online Reinforcement Learning

Yongjae Shin, Jongseong Chae, Jongeui Park, and Youngchul Sung

ICLR , 2026 , Rio de Janeiro, Brazil
Flow Actor-Critic for Offline Reinforcement Learning

Jongseong hae, Jongeui Park, Yongjae Shin, Gyeongmin Kim, Seungyul Han, and Youngchul Sung

ICLR , 2026 , Rio de Janeiro, Brazil
RL-Studio: A System for Multi-Phase Reinforcement Learning Experimentation

Whiyoung Jung, Sunghoon Hong, Deunsol Yoon, Yongjae Shin, Jeonghye Kim, Suhyun Jung, Hyundam Yoo, Youngjin Kim, Chanwoo Moon, Woohyung Lim, Soonyoung Lee, and Kanghoon Lee

AAAI Demonstration , 2026 , Singapore
Online Pre-Training for Offline-to-Online Reinforcement Learning

Yongjae Shin, Jeonghye Kim, Whiyoung Jung, Sunghoon Hong, Deunsol Yoon, Youngsoo Jang, Geon-Hyeong Kim, Jongseong Chae, Youngchul Sung, Kanghoon Lee, and Woohyung Lim

ICML , 2025 , Vancouver, Canada
Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data

Jeonghye Kim, Yongjae Shin, Whiyoung Jung, Sunghoon Hong, Deunsol Yoon, Youngchul Sung, Kanghoon Lee, and Woohyung Lim

ICML , 2025 , Vancouver, Canada

Spotlight
Sample-efficient and safe deep reinforcement learning via reset deep ensemble agents

Woojun Kim^*, Yongjae Shin^*, Jongeui Park, and Youngchul Sung

NeurIPS , 2023 , New Orleans, USA

* Equal Contribution