Jung-hun Kim (김정훈) [CV]
Postdoctoral Researcher at CREST, ENSAE Paris, FairPlay team
junghunkim7786@gmail.com | junghun.kim@ensae.fr
[Linkedin], [Google Scholar]
Research Overview
I work on online learning and decision-making, with a focus on bandit algorithms for matching, dynamic pricing, and recommendation. My research combines theoretical guarantees with practical insights, and has been published at ICML, NeurIPS, ICLR, and AISTATS.
Academic Positions
Postdoctoral Researcher, CREST, ENSAE Paris, FairPlay team, France
June 2025 - Present
Supervisor: Vianney PerchetPostdoctoral Researcher, IDIS, Seoul National University, South Korea
Sep 2023 - May 2025
Supervisor: Min-hwan OhPh.D. in Industrial and Systems Engineering, KAIST, South Korea
Sep 2018 - Aug 2023
Advisor: Se-Young YunResearch intern, Department of Statistics, London School of Economics, UK
Mar 2021 - Jul 2021
Supervisor: Milan Vojnović
Publications
Joe Suk, Jung-hun Kim
Jung-hun Kim, Min-hwan Oh
[NeurIPS 2024] Queueing Matching Bandits with Preference Feedback
Jung-hun Kim, Min-hwan Oh
[NeurIPS 2024] An Adaptive Approach for Infinitely Many-armed Bandits under Generalized Rotting Constraints
Jung-hun Kim, Milan Vojnović, Se-Young Yun
Jung-hun Kim, Se-Young Yun, Minchan Jeong, Junhyun Nam, Jinwoo Shin, Richard Combes
[ICML 2022] Rotting Infinitely Many-armed Bandits
Jung-hun Kim, Milan Vojnović, Se-Young Yun
[IEEE BigData 2018] Research Hypothesis Generation using Link Prediction in a Bipartite Graph
Jung-hun Kim, Aviv Segev
Working Papers
Matching Optimization + Preference Feedback
Jung-hun Kim, Min-hwan OhScheduling + Bilinear Rewards
Jung-hun Kim, Milan VojnovićSwitching Regret + Adversarial Bandits
Jung-hun Kim, Se-Young Yun
Academic Activities
Reviewer: NeurIPS, ICML, ICLR, AISTATS, JMLR, CDC, AAAI