Jaewoo Park
Department of Applied Statistics, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul, Republic of Korea, 03722
Office: Daewoo Hall 518
Email: jwpark88@yonsei.ac.kr
Phone: 02-2123-2540
Education
Ph.D. Statistics, Pennsylvania State University, 2019 (Thesis advisor: Dr. Murali Haran)
B.A. Economics and Applied Statistics, Yonsei University, 2013
Employment
Assistant Professor, Department of Applied Statistics, Yonsei University, September 2019 - present
Research Interest
Statistical computing, computational methods for intractable likelihoods
Bayesian deep learning, Gaussian process emulation
Modeling high-dimensional and non-Gaussian spatio-temporal data
Statistical methods for infectious disease research
Publications
*: corresponding author, ^: students supervised
Lee, H.^, Oh, D.^, Choi, S., and Park, J.* (2024) Bayesian Kriging Approaches for Spatial Functional Data. submitted
Kim, J., Lee, B., Min, C., Park, J., and Ryu, K. (2024) Density Estimation-based Stein Variational Gradient Descent. submitted
Yi, S.^, Kim, M.^, Park, J., Jeon, M., and Jin, IH. (2024) Impacts of Innovation School System in Korea: A Latent Space Item Response Model with Neyman-Scott Point Process. submitted
Cho, D.^, Chang, W., and Park, J. (2024) Fast Computer Model Calibration using Annealed and Transformed Variational Inference. Journal of Computational and Graphical Statistics. Accepted (Winner of the 2022 Korean International Statistical Society Outstanding Student Paper Award)
Jeon, Y.^, Chang, W., Jeong, S., Han, S., and Park, J.* (2024) A Bayesian Convolutional Neural Network-based Generalized Linear Model. Biometrics. 80(2), ujae057 (Winner of the 2022 Korean International Statistical Society Outstanding Student Paper Award)
Kang, H.B., Jung, Y.J.^, and Park, J.* (2024) Fast Bayesian Functional Regression for Non-Gaussian Spatial Data. Bayesian Analysis. 19(2), 407-438
Park, J.*, Yi, S.^, Chang, W., and Mateu, J. (2023) A Spatio-Temporal Dirichlet Process Mixture Model for Coronavirus Disease-19. Statistics in Medicine. 42(30), 5555-5576
Lee, B.S., and Park, J.* (2023) A Scalable Partitioned Approach to Model Massive Nonstationary Non-Gaussian Spatial Datasets. Technometrics, 65(1), 105-116
Lee, J., Kim, SH., Kim, Y.^, Park, J., Park, GE., and Kang, BJ. (2022) Radiomics nomogram: Prediction of 2-year disease-free survival in young age breast cancer. Cancers, 14(18), 4461
Park, J., Chang, W., and Choi, B. (2022) An Interaction Neyman-Scott Point Process Model for Coronavirus Disease-19. Spatial Statistics, 47, 100561
Park, J., Jeon, Y.^, Shin, M., Jeon, M., and Jin, IH. (2022) Bayesian Shrinkage for Functional Network Models, with Applications to Longitudinal Item Response Data. Journal of Computational and Graphical Statistics. 31(2), 360-377
Park, J.*, and Lee, S.^ (2022) A Projection-based Laplace Approximation for Spatial Latent Variable Models. Environmetrics, 33(1), e2703 (R package: fastLaplace)
Park, J., Schweinberger, M., and Jin, IH. (2022) Bayesian Model Selection for High-Dimensional Doubly-Intractable Posterior Distributions with Applications to Psychometrics. Computational Statistics and Data Analysis. 165, 107325
Park, J.*, and Haran, M. (2021) Reduced-dimensional Monte Carlo Maximum Likelihood for Latent Gaussian Random Field Models. Journal of Computational and Graphical Statistics, 30(2), 269-283
Park, J.* (2021) Bayesian Indirect Inference for Models with Intractable Normalizing Functions. Journal of Statistical Computation and Simulation, 91(2), 300-315
Park, J., and Haran, M. (2020) A Function Emulation Approach for Doubly Intractable Distributions. Journal of Computational and Graphical Statistics, 29(1), 66-77 (Winner of the 2018 Korean International Statistical Society Outstanding Student Paper Award)
Jung, M.C., Park, J., and Kim, S. (2019) Spatial Relationships between Urban Structure and Air Pollution in Korea. Sustainability, 11(2), 476
Goldstein, J., Park, J., Haran, M., Liebhold, A., and Bjornstad, O.N. (2019) Quantifying Spatio-Temporal Variation of Invasion Spread. Proceedings of the Royal Society B, 286(1894), 20182294
Park, J., and Haran, M. (2018) Bayesian Inference in the Presence of Intractable Normalizing Functions. Journal of the American Statistical Association, 113(523), 1372-1390
Park, J., Goldstein, J., Haran, M., and Ferrari, M. (2017) An Ensemble Approach to Predicting the Impact of Vaccination on Rotavirus Disease in Niger. Vaccine, 35(43), 5835-5841
Professional Service Activities
Associate Editor, Journal of Computational and Graphical Statistics, 2023 - present
Associate Editor, Communications for Statistical Applications and Methods, 2023 - present
Grants
Institute of Information & Communication Technology Planning & Evaluation (RS-2023-00259934), Development and Operation of Data Science Research and Education Program, Co-I, July 2023 - December 2027
Basic Research Laboratory, National Research Foundation of Korea (RS-2023-00217705), Analysis for High-dimensional Infectious Disease Data Based on AI and Bayesian Machine Learning, Co-I, June 2023 - June 2026
Young Scientist Grants, National Research Foundation of Korea (2020R1C1C1A0100386811), Computational Methods for High-Dimensional Spatial Data, PI, March 2020 - February 2025
Yonsei University Future-Leading Research Initiative (2019-22-0194), PI, September 2019 - September 2022
Projects
국립환경과학원, 환경위성 평균장 (L3) 알고리즘 고도화, Co-I, 2023
교육부, 코로나19 학생 확진현황 연구분석, Co-I, 2022
한국데이터산업진흥원, 코로나19 확진자 동선 및 소비 데이터를 활용한 감염병 확산에 대한 대국민 사전 알림 등 선제대응 체계 수립, PI, 2022
바이엘 코리아, 40세 미만 젊은 여성에서의 침습 유방암의 영상-유전적 특징: 선행연구, Co-I, 2022
Honors
Teaching Excellence Award, Yonsei University 2020, 2021, 2023
Korean International Statistical Society Outstanding Student Paper Award, "A Function Emulation Approach for Intractable Distributions," Joint Statistical Meeting 2018
Distinguished Graduate Fellowship, The Pennsylvania State University, 2014-2015
Teaching
Yonsei University
Functional Data Analysis (STA 6320), Fall 2019, 2020, Spring 2022-2024
Spatio-Temporal Data Analysis (STA 6241), Spring 2020, Fall 2021-2023
Bayesian Deep Learning (GEV6142), Fall 2023
Mathematical Statistics (STA6010), Spring 2021
Deep Learning (STA 3140), Fall 2019-2021, Spring 2022-2024
Bayesian Statistics (STA3105), Fall 2022-2024
Pennsylvania State University
Elementary Probability (STAT 318), Spring 2017
Statistical Concepts and Reasoning (STAT 100), Summer 2016
Elementary Statistics (STAT 200), Summer 2015
Students
I am looking for self-motivated Ph.D. students who are interested in the following areas: (1) computational methods for spatio-temporal data, (2) statistical methods for functional data, and (3) Bayesian deep learning algorithms. If you are interested in joining my research group, feel free to send me an email at jwpark88@yonsei.ac.kr. Please also see the list of current and past graduate students.