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JUNGTAEK KIM 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
- [April 2026] My collaborative paper "ReJump: A Tree-Jump Representation for Analyzing and Improving LLM Reasoning" with Yuchen Zeng, Shuibai Zhang, Wonjun Kang, Prof. Kangwook Lee, and others has been accepted at ICML-2026.
- [April 2026] My paper "Exploration and Exploitation Errors Are Measurable for Language Model Agents" with Jaden Park, Jongwon Jeong, Prof. Yong Jae Lee, and others has been released at arXiv.
- [March 2026] My paper "Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback" has been awarded a J2C Certification.
- [March 2026] My paper "Transformers in the Dark: Navigating Unknown Search Spaces via Bandit Feedback" with Prof. Kangwook Lee and others has been accepted at TMLR.
ABOUT ME
Jungtaek Kim is a research associate at the University of Wisconsin–Madison, working with Prof. Kangwook Lee. Previously, he was a postdoctoral associate at the University of Pittsburgh, working with Prof. Paul W. Leu and Prof. Oliver Hinder, and a postdoctoral researcher at POSTECH in the group of Prof. Minsu Cho. He received a B.S. in Mechanical Engineering and Computer Science and Engineering from POSTECH and a Ph.D. in Computer Science and Engineering from POSTECH, under the supervision of Prof. Seungjin Choi and Prof. Minsu Cho. During his Ph.D. program, he interned at Vector Institute and SigOpt (acquired by Intel). 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 a first author or co-author at top-tier machine learning conferences such as NeurIPS, ICML, AISTATS, UAI, and ICLR. He has also served as a program committee member or reviewer for several machine learning conferences. His main research interests are statistical machine learning, Bayesian optimization, and large language models.
CURRENT RESEARCH INTERESTS
- Statistical Machine Learning
- Bayesian Optimization
- Large Language Models
WORK-IN-PROGRESS PAPERS
- Jaden Park*, Jungtaek Kim*, Jongwon Jeong*, Robert D. Nowak, Kangwook Lee, and Yong Jae Lee. Exploration and Exploitation Errors Are Measurable for Language Model Agents.
- Jongwon Jeong, Jungtaek Kim, and Kangwook Lee. TAPE: Tool-Guided Adaptive Planning and Constrained Execution in Language Model Agents.
- Jungtaek Kim. Beyond Regrets: Geometric Metrics for Bayesian Optimization.
ELSEWHERE
- Academic Profile: Google Scholar, OpenReview, DBLP, Semantic Scholar, ORCID
- Social Media: LinkedIn, X
- Development: GitHub, Hugging Face
Last updated: May 21, 2026