Preprint
Kim and Shin (2025) Scalable and Efficient Multiple Imputation for Case-Cohort Studies via Influence Function-Based Supersampling.
arXiv:2511.14692.
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.
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.
Kim and Shin (2025) Scalable and Efficient Multiple Imputation for Case-Cohort Studies via Influence Function-Based Supersampling.
arXiv:2511.14692.
"Scalable and Efficient Multiple Imputation for Case-Cohort Studies via Influence Function-Based Supersampling"
"Multiple imputation for incomplete survival data with missing covariates: Toward valid causal inference"
[slides]