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Research Expertise & Professional Interests 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.
Self-Described Keywords Bayesian Methods and Computing Algorithms
Self-Described Keywords Bayesian Nonparametrics

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  • Bayesian
  • Methods
  • Computing
  • Algorithms