Jooho Kim
Portrait of Jooho Kim

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

View my CV (PDF).

Recent Works

Preprint

Preprint

Kim and Shin (2025) Scalable and Efficient Multiple Imputation for Case-Cohort Studies via Influence Function-Based Supersampling.
arXiv:2511.14692.

KSS Logo

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"

[slides]
Talk image

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

  • Fellowship for Fundamental Academic Fields, Seoul National University, 2024 & 2025
  • Graduate Research Fellowship in Science and Engineering, National Research Foundation of Korea (NRF), 2024 - 2025
  • Special Scholarship, Korea University, Fall 2022, Spring 2023
  • Semester High Honors, Korea University, Fall 2018, Spring 2022, Spring 2023
  • Agricultural Economics Alumni Scholarship, Department of Food and Resource Economics, Korea University, Spring 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