Chanmin Kim, PhD
Assistant Professor
Boston University School of Public Health
Dept of Biostatistics

PhD, University of Florida
MA, Columbia University

Chanmin Kim's work focuses on Bayesian (nonparametrics) methods, causal modeling (via machine learning methods) and mediation analysis, with application to environmental health statistics, health policy and behavioral science. Chanmin completed his PhD in Statistics at the University of Florida Gainesville, working on Bayesian methods for inference on the causal effects of mediation. He then joined the Department of Biostatistics at Harvard University, where he held a Research Associate position, and where he applied his Bayesian Nonparametric methods to evaluate the public health impact of air quality regulatory policies. 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, where he was invited to present his work. Chanmin sits in Crosstown 303.

2017 ASA: ASA Biometrics Section Paper Award
2015 NSF: Sackler Travel Award for the Sackler Colloquium, D.C.
2013 IASC: 1st Place, 2013 IASC Data Analysis Competition
2013 UF: GSC travel award
2013 UF: CLAS travel award
2012 SRCOS: Boyd Harshbarger Travel Award
2012 UF: CLAS travel award
2011 UF: Honorable Mention, NSF research day poster competition
2011 Centre de recherches mathematiques at University of Montreal: Travel Award for the Workshop on Causal Inference in Health Research, Canada
2011 UF: GSC travel award
2003 NEMO Partners consulting group: 3rd Place, HCG case competition
Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Faculty can login to make corrections and additions.

  1. Kim C, Daniels M, Li Y, Milbury K, Cohen L. A Bayesian semiparametric latent variable approach to causal mediation. Stat Med. 2017 Dec 18. PMID: 29250817.
  2. Zhang Z, Zheng C, Kim C, Van Poucke S, Lin S, Lan P. Causal mediation analysis in the context of clinical research. Ann Transl Med. 2016 Nov; 4(21):425. PMID: 27942516; DOI: 10.21037/atm.2016.11.11;.
  3. Kim C, Daniels MJ, Marcus BH, Roy JA. A framework for Bayesian nonparametric inference for causal effects of mediation. Biometrics. 2017 Jun; 73(2):401-409. PMID: 27479682; DOI: 10.1111/biom.12575;.
  4. Zigler CM, Kim C, Choirat C, Hansen JB, Wang Y, Hund L, Samet J, King G, Dominici F. Causal Inference Methods for Estimating Long-Term Health Effects of Air Quality Regulations. Res Rep Health Eff Inst. 2016 May; (187):5-49. PMID: 27526497.
  5. Perri MG, Limacher MC, von Castel-Roberts K, Daniels MJ, Durning PE, Janicke DM, Bobroff LB, Radcliff TA, Milsom VA, Kim C, Martin AD. Comparative effectiveness of three doses of weight-loss counseling: two-year findings from the rural LITE trial. Obesity (Silver Spring). 2014 Nov; 22(11):2293-300. PMID: 25376396; PMCID: PMC4225635; DOI: 10.1002/oby.20832;.
  6. Daniels MJ, Roy JA, Kim C, Hogan JW, Perri MG. Bayesian inference for the causal effect of mediation. Biometrics. 2012 Dec; 68(4):1028-36. PMID: 23005030; PMCID: PMC3927554; DOI: 10.1111/j.1541-0420.2012.01781.x;.

This graph shows the total number of publications by year, by first, middle/unknown, or last author.

Bar chart showing 6 publications over 4 distinct years, with a maximum of 3 publications in 2016

In addition to these self-described keywords below, a list of MeSH based concepts is available here.

Bayesian Method
Causal Inference
Mediation Analysis
Air Pollution Epidemiology
Environmental Health Sciences
Bayesian Nonparametrics
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715 Albany Street
Boston MA 02118
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