Sungkyu Jung
Professor of Statistics
Seoul National University
Interested in statistical theory and methods for Non-Euclidean, High-Dimensional data analysis, and Data Privacy
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:
Recent News (More news)
2025-06-29. A research paper on adaptive reference-guided estimation of high-dimensional PC subspace is accepted for publication in Stat. This work constitutes Dongsun’s masters thesis.
2025-06-10. Congratulations to Dr. Jaesung Park, who has successfully defended his PhD thesis “Sequential Dimension Reduction for Non-Euclidean data and its Strong Consistency.”
2025-03-20. The third edition of the classical statistics textbook “일반통계학 (Foundations of Statistics)” is now on sale. I coauthored this book with my colleagues from the department.
Last updated: June 29, 2025