Jung-hun Kim (김정훈) [CV]
Postdoctoral Researcher at CREST, ENSAE, IP Paris – FairPlay team
junghunkim7786@gmail.com | junghun.kim@ensae.fr
[Linkedin], [Google Scholar]

Research Overview 
I work on online learning and decision-making, with applications to matching, queueing systems, dynamic pricing, and recommendation.  My research combines theoretical guarantees with practical insights, and has been published at ICML, NeurIPS, ICLR, AISTATS, and TMLR.

Academic Positions

• Postdoctoral Researcher, CREST, ENSAE, IP Paris – FairPlay team, France
  June 2025 - Present
  Supervisor: Vianney Perchet

• Postdoctoral Researcher, IDIS, Seoul National University, South Korea
  Sep 2023 - May 2025
  Supervisor: Min-hwan Oh
  Research focus: Online learning for matching and dynamic pricing

• Ph.D. in Industrial and Systems Engineering, KAIST,  South Korea
  Sep 2018 - Aug 2023
  Advisor: Se-Young Yun
  Research focus: Online learning with non-stationary environments

• Research intern, Department of Statistics, London School of Economics, UK
  Mar 2021 - Jul 2021
  Supervisor: Milan Vojnović
  Research focus: Online learning with scheduling

Publications

• [TMLR 2025] Adversarial Bandits Against Arbitrary Strategies

Jung-hun Kim, Se-Young Yun 

• [NeurIPS 2025] Oracle-Efficient Combinatorial Semi-Bandits

Jung-hun Kim, Milan Vojnović, Min-hwan Oh 

• [ICML 2025] Tracking Most Significant Shifts in Infinite-Armed Bandits

Joe Suk, Jung-hun Kim

• [ICLR 2025] Dynamic Assortment Selection and Pricing with Censored Preference Feedback

    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 

• [AISTATS 2023] Contextual Linear Bandits under Noisy Features: Towards Bayesian Oracles

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 (link)
  Jung-hun Kim, Min-hwan Oh

• Scheduling + Bilinear Rewards (link)
  Jung-hun Kim, Milan Vojnović

Academic Activities

• • Reviewer: NeurIPS, ICML, ICLR, AISTATS, JMLR, CDC, and AAAI