Professor

Principal Investigator


  Wonil Chung, Ph.D.
  Associate Professor in Statistics
  Department of Statistics and Actuarial Science
  Soongsil University



Information

Address: 369 Sangdo-Ro, Dongjak-Gu, Baird Hall 511, Soongsil University, Seoul, Korea 06978
Tel: +82-2-820-0441
Email : wchung (at) ssu.ac.kr
URL: http://statistics.ssu.ac.kr/~wchung

Research Interest

Biostatistics, Statistical Genetics, Statistical Computing,
Big Data Analysis, Statistical Learning, Deep Learning, Bayesian Statistics,
Polygenic Prediction, GWAS Studies, Transcriptomics, Methylomics, Metabolomics

Education and Training

Research Associate, Harvard T.H. Chan School of Public Health, Boston, USA
Ph.D. in Biostatistics, University of North Carolina at Chapel Hill, USA (2013)
M.S. in Statistics, Seoul National University, Seoul, Korea (2008)
B.S. in Statistics, Seoul National University, Seoul, Korea (2006)

Grants

Mid-Career Researcher Program, NRF Fund (2025-2028)
Global - Learning & Academic research institution for Masters, PhD students, and Postdocs (G-LAMP), NRF Fund (2025-2030)
Basic Science Research Program, NRF Fund (2021-2030)
Core Technology Development Program for Infectious Disease Response Platforms, NRF Fund (2021-2025)
Young Investigator Program, NRF Fund (2020-2025)

Awards

Natural Science Award (2020), Soongsil University, Seoul, Korea
Charles J. Epstein Trainee Award for Excellence in Human Genetics Research-Semifinalist (2018), ASHG, MD, USA
Nguyen V. Dat Excellence Award (2008), University of North Carolina at Chapel Hill, USA

Editor

Genomics and Informatics, Associate Editor (2023-Present)

Professional Affiliations

National Bioethics Policy Institute, DTC Certification Review Committee, Committee Member (2022-Present)
Korean Statistical Society (KSS), Council Member (2023-Present)
Korean Genome Organization (KOGO), Executive Committee Member (2023-Present)
American Statistical Association (ASA), Regular Member
American Society of Human Genetics (ASHG), Regular Member

Teaching

Regression Analysis, Categorical Data Analysis, Data Mining, Deep Learning, Statistical Computing
Linear Models, Statistical Learning, Information Theory