Juyeon Kim
Juyeon Kim
My research focuses on causal inference, particularly on methodological problems related to the design of credible causal comparisons. My current work includes quantifying overlap in observational studies and methodological work on matching. I am also motivated by real-world applications across diverse scientific domains, with current applied work involving maritime transportation data. My broader interests include heterogeneous treatment effects and experimental design.
Education
- Ph.D. in Statistics, Seoul National University, Sep 2024 - Present.
- B.S. in Statistics & Computer Science and Engineering, Seoul National University, Mar 2020 - Aug 2024.
Publications
- Dongmin Bang†, Juyeon Kim†, Haerin Song, and Sun Kim (2025). ADME-drug-likeness: enriching molecular foundation models via pharmacokinetics-guided multi-task learning for drug-likeness prediction. Bioinformatics, 41(Suppl. 1), i352–i361. https://doi.org/10.1093/bioinformatics/btaf259
† Co-first authors.
Presentations
- Geondo Park, Juyeon Kim, and Kwonsang Lee. Quantifying overlap in causal inference via integrated KL projections. 2026 American Causal Inference Conference (ACIC), Salt Lake City. [Poster]
- Geondo Park, Juyeon Kim, and Kwonsang Lee. Quantifying overlap in causal inference via integrated KL projections. 2026 European Causal Inference Meeting (EuroCIM), Oxford. [Poster]
- Geondo Park, Juyeon Kim, and Kwonsang Lee. Quantifying overlap in causal inference: A framework for early-stage assessment. 2025 Korean Statistical Society (KSS) Summer Conference, Gyeongju. [Poster]
Teaching Assistant
- Statistics (F32.102), Fall 2026.
- Regression Analysis and Lab (326.313) / Regression Models 1 (M3635.000400), Spring 2026.
- Research Method and Statistics (M2480.002400), Spring 2025.
- Statistical Computing and Lab (326.212), Fall 2024.