Students

Current Students

[C1]  Soyun Jeon, Ph.D Student (Spring 2023 - present)

[C2]  Jiwon An, Ph.D Student (Fall 2025 - present)

[C3]  Soomin Choi, M.S. Student (Spring 2024 - present)

[C4]  Yoonseul Choi, M.S. Student (Spring 2024 - present)

[C5]  Seung Jun Park, M.S. Student (Spring 2024 - present)

[C6]  Yeonsu Kim, M.S. Student (Spring 2025 - present)

[C7]  Chang Ju Kong, M.S. Student (Spring 2025 - present)

Alumni

[A22]  Byunghyeon Song, M.S. in Applied Statistics, August 2025

        Thesis:  Uncertainty quantification in spatio-temporal forecasting via conditional diffusion model

[A21]  Jiwon An, M.S. in Applied Statistics, August 2025

        Thesis:  Bivariate spatio-temporal mixture modeling of chronic disease prevalence in South Korea

[A20]  Seonghan Lee, M.S. in Applied Statistics, August 2025

        Thesis:  A bivariate Bayesian spatio-temporal analysis of traffic accidents in Seoul: Comparing alternative definitions of spatial adjacency matrices

[A19]  Heejun Jeon, M.S. in Applied Statistics, February 2025

        Thesis:  Investigating the impact of spatial and tail dependencies on joint spatial quantile regression

[A18]  Wook Jin Son, M.S. in Applied Statistics, February 2024

        Thesis:  Bayesian bivariate spatial modeling using Seoul public transportation data

[A17]  Jiwon Park, M.S. in Applied Statistics, August 2023

        Thesis: Analysis of the usage patterns of public bikes in Seoul with clustering and the spatial model

[A16]  Soyun Jeon, M.S. in Applied Statistics, February 2023

        Thesis: Spatio-temporal copula modeling for extreme air pollutant data in Korea

[A15]  Jisoo Lee, M.S. in Applied Statistics, February 2023

        Thesis: Prediction of COVID-19 confirmed cases in Seoul by using bayesian network

[A14]  Jaeseun Lee, M.S. in Applied Statistics, February 2023

        Thesis: Bayesian spatially-clustered coefficient model with temporal structures

[A13]  Jong Hwan Hong, M.S. in Applied Statistics, February 2022

        Thesis: Bayesian spatio-temporal model for COVID-19 data in Seoul

[A12]  Jeewoong Jeong, M.S. in Applied Statistics, February 2022

        Thesis: Comparative analysis of the recommendation system using matrix factorization

[A11]  Dayun Kang, M.S. in Applied Statistics, February 2017 &  & Ph.D. in Applied Statistics, August 2021

        Thesis: Bayesian zero-inflated spatio-temporal modeling of scrub typhus data in Korea

        Dissertation:  Bayesian spatial clustering of a regression coefficient for epidemiological data

[A10]  Younghoo Do, M.S. in Applied Statistics, February 2020

        Thesis: A study on image segmentation using metropolis algorithm : focused on α-granule Images of platelets

[A9]  Hyunho Choi, M.S. in Applied Statistics, February 2020

        Thesis: Spatio-temporal early detection algorithm for hepatitis a data in South Korea

[A8]  Seong Ju Kim, M.S. in Applied Statistics, February 2020

        Thesis: RTC-Random forest model for sepsis early detection in CBC data

[A7]  KangHyuck Lee, M.S. in Applied Statistics, February 2020

        Thesis:  Oversampling based on Gaussian Mixture Model for Imbalanced data classification

[A6]  JinHyung Mok, M.S. in Applied Statistics, August 2019

        Thesis: Analysis of Sepsis data using imputation methods and Random Forest model

[A5]  Hwa Young Jeong, M.S. in Applied Statistics, February 2019

        Thesis: Bayesian spatio-temporal SIR model for epidemic data in Korea

[A4]  Yu Jin Jang, M.S. in Applied Statistics, February 2019

        Thesis: A comparison study of spatial copula model in extreme areal data

[A3]  Chaesung Lim, M.S. in Applied Statistics, February 2019

        Thesis: Bayesian spatio-temporal modeling of traffic accidents in Seoul, Korea

[A2]  PilGeun Jin,  M.S. in Applied Statistics, February 2018

        Thesis: Bayesian spatial multilevel analysis of mental health with R-INLA

[A1]  Sojin Hong, M.S. in Applied Statistics, February 2017

        Thesis: Bayesian clustering methods of spatially dependent regression coefficients