Professor of Statistics

Seoul National University

Interested in statistical theory and methods for Non-Euclidean, High-Dimensional data analysis, and Data Privacy

My publications Courses Lab

Brief Biography

I am a Professor of Statistics at the Seoul National University. Before I joined Seoul National University, I spent seven years at the University of Pittsburgh, after completing my PhD at the University of North Carolina at Chapel Hill.

Research interest lies in the theoretical study and applications of modern Statistics and Data Science in the analysis of data that lie on non-standard spaces. This context includes the high-dimension, low-sample-size (HDLSS) situation, non-Euclidean data analysis, the interplay between geometry and statistics, and data fusion. In particular, models and methodologies for dimension reduction, visualization of important variation and hypothesis testings need to be developed with special care for these modern data situations. Particular applications include analysis of directions, landmark-based and skeletally-modeled object shapes, data in stratified spaces or from multiple sources, and retrieving low-dimensional geometric structures in high-dimensional data. I am also interested in statistical issues in Data Privacy, including Differential Privacy and Synthetic Data Generation.

I have authored two books and coauthored one more, all in Korean: book art book art book art

Recent News (More news)

  • 2026-02-02. An article revealing general conditions for existence and uniqueness of M-functionals and M-estimators on Riemannian manifolds, joint work with Dr. Jongmin Lee, is published in SPL.

  • 2026-01-29. Meet the ‘Huber mean’ at Significance!

  • 2025-12-19. The department of Statistics and Institute for Data Innovation in Science of Seoul National University are co-hosting the 2025 Winter Conference of Korean Statistical Society on December 19–20, 2025 at Seoul National University.

  • Last updated: February 18, 2026