Professor of Statistics
Seoul National University
Interested in statistical theory and methods for Non-Euclidean, High-Dimensional data analysis, and Data Privacy
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.
2024-11-14. I gave a keynote speech at the JMP Discovery Summit Korea 2024 and am making the slides I used publicly available.
2024-10-24. I am happy to announce that an UTFORSK grant from Norwegian Directorate for Higher Education and Skills is awarded for the full four years of 2025–2028. This project is to increase research and education activities in Statistics of Complex Data (ScoDa) and is a joint grant between Universitetet i Stavanger (Professor Joern Schulz as PI) and SNU, as the main foreign partner.
2024-10-17. I am actively participating in the Interactions of Geometry and Statistics (ISAG) II workshop, IMS, NUS, in Singapore from Oct. 17 to Oct. 25.
Last updated: November 14, 2024