I am a Senior Researcher at the Institute for Data Innovation in Science, Seoul National University (Mentor: Sungkyu Jung). I develop nonparametric regression and inference methods for manifold-valued and metric-space data, with particular emphasis on Fréchet regression, geometric predictors, and distributional data. I received my Ph.D. in Statistics from Seoul National University in February 2025 under the supervision of Byeong U. Park.
Fréchet Regression | Nonparametric Analysis | Non-Euclidean Data | Functional Data Analysis
A Note on a Local Entropy Condition in the Wasserstein Space (co-author: Jeong Min Jeon, Byeong U. Park, under revision at Statistics & Probability Letters)
Local Fréchet regression with Riemannian predictors (co-author: Jeong Min Jeon, arXiv preprint)
Functional Principal Component Analysis for Manifold-Indexed Data (co-author: Jeong Min Jeon, arXiv preprint)
Robust Local Fréchet regression: Nonasymptotic Theory and Minimax Optimality (co-author: Daisuke Kurisu, Submitted manuscript)
Semiparametric Regression (co-author: Daisuke Kurisu and Alexander Petersen)
Parametric Regression (co-author: Shogo Kato and Sungkyu Jung)
Chart-Induced Global Fréchet Regression
Seminar at the Institute of Statistical Mathematics (2026) - Oral Presentation (Invited by Shogo Kato)
Local Fréchet Regression with Riemannian Predictors
The 1st Asian New Researchers Conference (2026) - Oral and Poster Presentation
The Summer Conference of the Korean Statistical Society (2026) - Oral Presentation
The IMS Annual Meeting (2026) - Oral Presentation (Invited by Yaqing Chen and Paromita Dubey)
The New Researchers Conference (2026) - Oral Presentation
International Conference on Econometrics and Statistics (EcoSta 2026) - Oral Presentation (Invited by Thanh Mai Pham Ngoc)
Statistical Foundations for the Analysis of Non-Euclidean Data (IMSI 2026) - Oral and Poster Presentation
Local Fréchet Regression with Toroidal Predictors
1st International New Researchers Conference (1st INRC, 2025) - Oral Presentation
Seminar at Kyushu University (2026) - Oral Presentation (Invited by Yuichi Goto)
The 18th MSJ-SI on MMS (2026) - Poster Presentation
The 20th Spring Meeting of the Japan Statistical Society (2026) - Poster Presentation
The 26th Workshop on Nonparametric Statistical Analysis and Bayesian Statistics (2026) - Oral Presentation (Invited by Yasuhito Tsuruta)
The Applied Statistics Workshop at the University of Tokyo (2026) - Oral Presentation (Invited by Daisuke Kurisu)
IMS-APRM 2026 at The Chinese University of Hong Kong (2026) - Poster Presentation
Local Fréchet Regression with Spherical Predictors
8th International Conference on the Science of Data Science (ICSDS 2025) - Oral Presentation
International Conference on Econometrics and Statistics (EcoSta 2025) - Oral Presentation (Invited by Jeong Min Jeon)
Korean Statistical Society Winter Conference (2024) - Oral Presentation
Oral presentation at ICSDS 2025, Seville. Special thanks to Changwon Choi (Postdoctoral Researcher at Seoul National University) for the photo.
Oral presentation at The 26th Workshop on Nonparametric Statistical Analysis and Bayesian Statistics, Meiji University, Tokyo. Special thanks to Yongjae Kim (Postdoctoral Researcher at Seoul National University) for the photo.
Sejong Science Fellowship - National Research Foundation of Korea (NRF)
Principal Investigator (Mar. 2025 – Present)
Project: Development of Structural Nonparametric Models for Non-Euclidean Data
Funded by the Ministry of Science and ICT, Republic of Korea (No. RS-2025-00515381)
Brigham Young University (BYU)
Visiting scholar, Department of Statistics (Sep. 2026 - Aug. 2027)
Host: Alexander Petersen
Institute for Mathematical and Statistical Innovation (IMSI)
Participant, Long Program on Connectomics: Non-Euclidean Data Analysis for Brain Structure and Function (Sep. - Oct. 2026)
The 20th Spring Meeting of the Japan Statistical Society (2026)
Korean Statistical Society Winter Conference (2024)
Commendation Award
A one-page summary of 'Local Fréchet regression with Riemannian predictors' is available.