About

Seoncheol Park

Now I am an assistant professor at the Department of Mathematics and the Department of Applied Statistics at Hanyang University, South Korea. Before joining Hanyang University, I worked as an assistant professor at the Department of Information Statistics, Chungbuk National University for two years. Also, I was a post-doctoral research fellow at the Pacific Climate Impacts Consortium under the supervision of Prof. Francis Zwiers. I received my Ph.D. degree in statistics at Seoul National University under the supervision of Prof. Hee-Seok Oh. I was also a member of Multiscale Methods in Statistics Lab.

Professional Experiences

Education

  • Ph.D., Statistics, Seoul National University, Seoul, Korea, 2019.

  • B.S., Mathematical Sciences (Double Major with Management Sciences), KAIST, Daejeon, Korea, 2013.

Research Interests

  • Spatio-temporal data analysis and extreme value statistics, application to environmental and public health data

Academic Works

International Journal Papers

(\({}^\ast\): Corresponding author, and \({}^{\ast\ast}\): Students I supervised)

  1. H. Lee, D. Kwon, S. Park, S-R. Park, , D. Chung and J. Ha\({}^\ast\) (2023). Temporal association between age-specific incidence of Guillain–Barré syndrome and SARS-CoV-2 vaccination; a nationwide time-series correlation study, Osong Public Health and Research Perspectives, 14(3), 224–231.

  2. J. Lee\({}^{\ast\ast}\) and S. Park\({}^\ast\) (2023). Prediction of sharp change of particulate matter in Seoul via quantile mapping, Communications for Statistical Applications and Methods, 30(3), 259–272.

  3. B. Lee\({}^{\ast\ast}\), P. Yeon and S. Park\({}^\ast\) (2022). The factors and relationships influencing urban hiking exercise characteristics after COVID-19 occurrence: at Seoul Metropolitan Area and in their 20s and 30s, International Journal of Environmental Research and Public Health, 19(24), 16403.

  4. S. Cho, Y-M. Kim, G. Seong, S. Park, S. Park, S-E. Lee and Y. Park\({}^\ast\) (2022). Analysis of on-ship transmission through cases of COVID-19 mass outbreak on Republic of Korea Navy Amphibious Warfare ship. Epidemiology and Health, 44, e2022065.

  5. S. Lee, S. Park and Y. Lim\({}^\ast\) (2022). Prediction of extreme PM2.5 concentrations via extreme quantile regression. Communications for Statistical Applications and Methods, 29(3), 319–331.

  6. S. Park and H-S. Oh\({}^\ast\) (2022). Lifting scheme for streamflow data in river networks. Journal of the Royal Statistical Society: Series C (Applied Statistics), 71(2), 467–490.

  7. J. Kim, S. Park\({}^\ast\), J. Kwon, Y. Lim and H-S. Oh (2021). Estimation of spatio-temporal extreme distribution using a quantile factor model. Extremes, 24(1), 177–195.

  8. S. Park\({}^\ast\), J. Kwon, J. Kim and H-S. Oh (2018). Prediction of extremal precipitation by quantile regression forests: from SNU Multiscale team. Extremes, 21(3), 463–476.

  9. S. Park and H-S. Oh\({}^\ast\) (2017). Spatio-temporal analysis of particulate matter extremes in Seoul: use of multiscale approach. Stochastic Environmental Research and Risk Assessment, 31(9), 2401–2414.

  1. Spatial statistical models for environmental data in Korea, Japanese Joint Statistical Meeting 2022, Tokyo, Japan, September 2022.

  2. Lifting scheme for streamflow data in river networks, 2022 The Korean Data Information Science Society Spring Conference, Busan, Korea, May 2022.

  3. Lifting scheme for streamflow data in river networks, 2021 The Korean Statistical Society Autumn Conference, Seoul, Korea, November 2021.

  4. Lifting scheme for streamflow data in river networks, Bernoulli-IMS 10th World Congress in Probability and Statistics, Seoul, Korea, July 2021.

  5. A new approach for modelling the spatial extent of agricultural drought, The 55th Canadian Meteorological and Oceanographic Society (CMOS) Congress, Victoria, Canada, June 2021.

  6. Multiresolution analysis for spatio-temporal data, 5th Institute of Mathematical Statistics Asia Pacific Rim Meeting, Singapore, Singapore, June 2018.

  7. Prediction of extremal precipitation: the use of quantile regression forests, 10th Extreme Value Analysis Conference, Delft, Netherlands, June 2017.

  8. Multiresolution analysis for spatio-temporal data. 2017 The Korean Statistical Society Spring Conference, Seoul, Korea, May 2017.

  9. Multiscale modeling for particulate matter extremes. 2015 The Korean Statistical Society Autumn Conference, Yongin, Korea, November 2015.

  10. Multiscale modeling for particulate matter extremes in Seoul. The Seoul Institute Research Competition 2015, Seoul, Korea, November 2015.

  11. Prediction of extreme particulate matter : the use of quantile regression forests. 2014 The Korean Statistical Society Autumn Conference, Seoul, Korea, November 2014.

  1. Excellence award (3rd place), KSIAM-MathWorks problem challenge, Korea Society for Industrial and Applied Mathematics, Sep 2018.

  2. Best oral presentation award (Pre-PhD): Multiresolution analysis for spatio-temporal data. The Korean Statistical Society, May 2017.

  3. Excellence award, The Seoul Institute Research Competition 2015, The Seoul Institute, November 2015.

International or Domestic Research Foundations

  • Basic Science Research Program (기본연구), Korean Ministry of Education, June 2021 ~ August 2024.

University Grants

  • 신임교원 정착 연구 지원사업, Hanyang University (HYU), March 2023 ~ August 2024.

  • 신진교수 연구비 지원사업, Chungbuk National University (CBNU), March 2021 ~ August 2022.

Scholarship

  • Sohn Dong-Joon Scholarship, College of Natural Sciences (SNU), May 2016 ~ August 2019.

  • Theoretical and Applied Climatology

  • Annals of Applied Statistics

  • Journal of Agricultural, Biological and Environmental Statistics

  • Extremes

  • Stochastic Environmental Research and Risk Assessment

  • Computational Statistics

  • Journal of the Korean Statistical Society

  • Communications for Statistical Applications and Methods

  • Computational Statistics and Data Analysis

Hanyang University

Undergraduate Courses

  • Introduction to Regression Analysis (2024 Spring)

  • Computational Statistics (2023 Fall)

  • Artificial Intelligence and Machine Learning (2023 Spring, 2024 Spring)

Graduate Courses

  • Regression Analysis (2024 Spring)

  • Statistical Data Science (2023 Fall)

  • Seminar in Recent Development of Applied Statistics (2023 Spring)

Chungbuk National University

Undergraduate Courses

  • Elementary Probability Theory (2022 Spring)

  • Regression Analysis (2021 Spring, 2022 Spring)

  • Statistical Simulation (2021 Spring)

  • Insurance Statistics (2021 Fall)

  • Financial Statistics (2021 Fall)

  • Financial and Insurance Statistics (2022 Fall)

  • Spatial Statistics (2022 Fall)

Graduate Courses

  • Topics in Regression Analysis (2022 Spring)

  • Statistical Methodology (2021 Spring)

  • Machine Learning Methodology (2022 Fall)

  • Deep Learning (2021 Fall)

Contact Me

pscstat@hanyang.ac.kr or pscstat@gmail.com