Chanmin Kim, PhD

Assistant Professor, Biostatistics
Chanmin Kim


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.


  • University of Florida, PhD
  • Columbia University, MA
  • Sogang University, BBA

Classes Taught

  • SPHBS730


  • Published on 12/18/2018

    Yan Liu, Henrike Besche, Audrey Beliveau, Xingyu Zhang, Edward Kroc, Melanie Stefan, Johanna Gutlerner, Chanmin Kim. Challenges from Modeling Open Online Assessment Data. In JSM 2018 Proceedings, Statistical Computing Section. American Statistical Association. Alexandria, VA. 2018; 1121-1131.

  • Published on 7/11/2018

    Shruthi Mahalingaiah, Kevin J. Lane, Chanmin Kim, J. Jojo Cheng, Jaime E. Hart. Impacts of Air Pollution on Gynecologic Disease: Infertility, Menstrual Irregularity, Uterine Fibroids, and Endometriosis: a Systematic Review and Commentary. Current Epidemiology Reports. 2018; 5(3):197-204.

  • Published on 2/23/2018

    Yan Liu, Chanmin Kim, Amery D. Wu, Paul Gustafson, Edward Kroc, Bruno D. Zumbo. Investigating the Performance of Propensity Score Approaches for Differential Item Functioning Analysis (to appear). Journal of Modern Applied Statistical Methods. 2018.

  • Published on 12/18/2017

    Kim C, Daniels M, Li Y, Milbury K, Cohen L. A Bayesian semiparametric latent variable approach to causal mediation. Stat Med. 2018 Mar 30; 37(7):1149-1161. PMID: 29250817.

    Read at: PubMed
  • Published on 11/1/2016

    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.

    Read at: PubMed
  • Published on 8/1/2016

    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.

    Read at: PubMed
  • Published on 5/1/2016

    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.

    Read at: PubMed
  • Published on 11/1/2014

    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.

    Read at: PubMed
  • Published on 9/24/2012

    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.

    Read at: PubMed