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JUNGTAEK KIM Postdoctoral Research Associate jungtaek.kim [at] wisc [dot] edu Google Scholar · GitHub · X · LinkedIn · Curriculum Vitae |
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HOME · DETAILED PROFILE · ARCHIVES · PUBLICATIONS: COMPLETE LIST
NEWS
- [May 2025] My two papers "Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning" and "VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data" have been accepted at ICML-2025.
- [February 2025] My collaborative paper "VersaPRM: Multi-Domain Process Reward Model via Synthetic Reasoning Data" with Thomas Zeng, Prof. Kangwook Lee, and others is released at arXiv.
- [January 2025] Happy new year!
- [November 2024] After a wonderful time at the University of Pittsburgh, I am joining the University of Wisconsin–Madison as a postdoctoral research associate working with Prof. Kangwook Lee.
- [October 2024] My collaborative paper "Discovering Multi-Layer Films for Electromagnetic Interference Shielding and Passive Cooling with Multi-Objective Active Learning" has been accepted at NeurIPS Workshop on AI for Accelerated Materials Discovery (AI4Mat-2024).
- [September 2024] My paper "Model Fusion through Bayesian Optimization in Language Model Fine-Tuning" has been accepted at NeurIPS-2024.
- [September 2024] My paper "Budget-Aware Sequential Brick Assembly with Efficient Constraint Satisfaction" has been accepted at TMLR.
ABOUT ME
Jungtaek Kim is a postdoctoral research associate at the University of Wisconsin–Madison, working with Prof. Kangwook Lee. Before that, he was a postdoctoral associate at the University of Pittsburgh, working with Prof. Paul W. Leu, Prof. Satish Iyengar, Prof. Lucas Mentch, and Prof. Oliver Hinder, and a postdoctoral researcher at POSTECH, in the group of Prof. Minsu Cho. He received B.S. in Mechanical Engineering and Computer Science and Engineering from POSTECH in 2015, and Ph.D. in Computer Science and Engineering from POSTECH in 2022, under the supervision of Prof. Seungjin Choi and Prof. Minsu Cho. He interned at Vector Institute and SigOpt (acquired by Intel), during his Ph.D. program. His internship at Vector Institute was carried out under the supervision of Prof. Graham W. Taylor and he worked with Dr. Michael McCourt at SigOpt. He presented his work as the first author or a co-author, at the top-tier machine learning conferences such as NeurIPS, ICML, AISTATS, UAI, and ICLR, and moreover he served as a program committee member or a reviewer for diverse machine learning conferences such as NeurIPS, ICML, AISTATS, UAI, and ICLR. His main research interests are statistical machine learning, Bayesian optimization, large language models, and sequential assembly.
CURRENT RESEARCH INTERESTS
- Statistical Machine Learning
- Bayesian Optimization
- Sequential Assembly
WORK-IN-PROGRESS PAPERS
- Jungtaek Kim. Beyond Regrets: Geometric Metrics for Bayesian Optimization.
ELSEWHERE
- Academic Profile: Google Scholar, DBLP, Semantic Scholar, ORCID
- Social Network: LinkedIn, X
- Development: GitHub
Last updated: June 26, 2025