Heewoong Choi

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I’m a Ph.D. student at Seoul National University advised by Taesup Moon.

My primary research interest lies in developing scalable reinforcement learning (RL) algorithms, focusing on (1) improving performance as more data becomes available and (2) enabling generalization over long horizons.

Recently, I have been interested in extending the domain by leveraging offline RL to train large language models (LLMs) in multi-turn settings.

               

Education

Mar. 2023 - Present
Seoul National University
Ph.D. student in Electrical and Computer Engineering
Mar. 2017 - Feb. 2023
Seoul National University
B.S. in Electrical and Computer Engineering
Leave of absence for military service (Mar. 2019 - Feb. 2021)

Publications

(*: equal contribution)
[C4] Option-aware Temporally Abstracted Value for Offline Goal-Conditioned Reinforcement Learning
NeurIPS 2025 (Spotlight)
[C3] Genomic Data Classification via Universal Compression
ISMB/ECCB 2025
[C2] Listwise Reward Estimation for Offline Preference-based Reinforcement Learning
ICML 2024
[C1] NCIS: Neural Contextual Iterative Smoothing for Purifying Adversarial Perturbations
WACV 2024

Work Experience

Jun. 2022 - Nov. 2022
NAVER CLOVA, AI engineer intern at CLOVA Image-Vision team
Developed a head pose estimation model for real-time applications.

Honors

Mar. 2017 - Feb. 2023
Presidential Science Scholarship
Full enrollment fee from Korea Student Aid Foundation (KOSAF)