Preprint
Kim and Shin (2025) Scalable and Efficient Multiple Imputation for Case-Cohort Studies via Influence Function-Based Supersampling.
arXiv:2511.14692.
Jooho Kim
Hi, welcome to my website. I am a master’s student in the Department of Statistics at Seoul National University, advised by Professor Yei Eun Shin. My research focuses on multiple imputation for missing covariates in survival analysis under two-phase sampling designs, such as case-cohort and nested case-control studies. My master’s research is supported by a graduate fellowship from the National Research Foundation of Korea. Previously, I received my Bachelor’s degree in Food and Resource Economics and Statistics from Korea University.
Research Interests
My primary methodological interests are in missing data, survival analysis, and causal inference.
I am also broadly interested in statistical machine learning, including uncertainty quantification in deep learning models.
CV
Recent Works
Presentation at the 2025 Winter Conference of the Korean Statistical Society
"Scalable and Efficient Multiple Imputation for Case-Cohort Studies via Influence Function-Based Supersampling"
Recipient of the Graduate Student Paper Award
[slides]
Presentation at the 2nd Symposium on Causal Inference
"Multiple imputation for incomplete survival data with missing covariates: Toward valid causal inference"
[slides]Honors and Awards
- Graduate Student Paper Award, Korean Statistical Society, Dec. 2025
- Fellowship for Fundamental Academic Fields, Seoul National University, May 2024; Feb. 2025
- Graduate Research Fellowship in Science and Engineering, National Research Foundation of Korea, Sep. 2024 - Aug. 2025
- Special Scholarship, Korea University, Sep. 2022; Mar. 2023
- Semester High Honors, Korea University, Sep. 2018; Mar. 2022; Mar. 2023
- Agricultural Economics Alumni Scholarship, Department of Food and Resource Economics, Korea University, Mar. 2022
Teaching
Teaching Assistant at Seoul National University
- Fall 2025: Survival Data Analysis and Lab
- Spring 2025: Selected Topics Seminar
- Fall 2024: Mathematical Statistics 2
- Spring 2024: Statistics Lab