Yongjae Shin

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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.

Publications

  1. 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
  2. Flow Actor-Critic for Offline Reinforcement Learning
    Jongseong Chae, Jongeui Park, Yongjae Shin, Gyeongmin Kim, Seungyul Han, and Youngchul Sung
    ICLR , 2026 , Rio de Janeiro, Brazil
  3. RL-Studio: A System for Multi-Phase Reinforcement Learning Experimentation
    Whiyoung Jung, Sunghoon Hong, Deunsol Yoon, Jeonghye Kim, Yongjae Shin, Suhyun Jung, Hyundam Yoo, Youngjin Kim, Chanwoo Moon, Woohyung Lim, Soonyoung Lee, and Kanghoon Lee
    AAAI Demonstration , 2026 , Singapore
  4. 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
  5. 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
  6. 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