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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 (중견연구), 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 (기초과학연구), NRF Fund (2021-2030)
Core Technology Development Program for Infectious Disease Response Platforms (감염병연구), NRF Fund (2021-2025)
Young Investigator Program (신진연구), 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, NC, USA

Editor

Genomics and Informatics, Associate Editor (2023-Present)

Professional Affiliations

Korean National Institute for Bioethics Policy (국가생명윤리정책원 DTC 항목검토위원회), 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