Chanmin Kim, an Associate Professor of Statistics at SungKyunKwan University (SKKU, Seoul, Korea), is a statistician whose research interests span Bayesian nonparametric/semiparametric methodologies, causal modelling, machine learning, and their applications in health science, health policy evaluation, and air pollution epidemiology. His reasearch also sits at the intersection of data science, data visualization and efficient computation algorithm for Bayesian models. He has extensive experience in handling/analyzing massive and scalable data such as Medicare/Medicaid data, real-time air pollution and monitoring data in the US.

Prior to joining SKKU, he was an assistant professor of Biostatistics at Boston University and spent several years at Harvard Biostatistics as a research fellow/associate (working with Dr. Corwin Zigler) where he applied his Bayesian Nonparametric methods to evaluate the public health impact of air quality regulatory policies. He got his MA in Statistics from Columbia University and PhD in Statistics from the University of Florida (supervised by Dr. Michael Daniels) He is the recipient of many awards for his doctoral and post-doctoral work, including the prestigious Biometrics section Paper award at the Joint Statistical Meetings in 2017 and the Mitchell Prize (2nd place) in 2020 from the International Society of Bayesian Analysis.

Education/Positions

Assistant/Associate Professor, Statistics, SungKyunKwan University, 2020-current

Assistant Professor, Biostatistics, Boston University, 2017-2019

Adjunct Assistant Professor, Biostatistics, Boston University, 2020-2023

Research Associate, Biostatistics, Harvard University, 2016-2017

Research Fellow, Biostatistics, Harvard University, 2014-2017

Postdoctoral Fellow, Statistics, University of Texas, Austin, 2013-2014

Ph.D. in Statistics, University of Florida, Gainesville, 2013

M.A. in Statistics, Columbia University, New York, 2008

B.A. in History / B.B.A. in Business, Sogang University, Seoul, 2006