Seongwon Im, PhD

• Ph.D., Colorado State University, Fort Collins, CO
• M.S., Colorado State University, Fort Collins, CO
• B.S., St. Lawrence University, Canton, NY

View CV

Research interests

• Bayesian nonparametric modeling
• Distributed lag model for mixture exposures
• Public health applications, with a focus on air pollution

Publications

• Im S, Wilson A, and Mork D. 2025. Structured Bayesian Regression Tree Models for Estimating Distributed Lag Effects: The R Package dlmtree. arXiv preprint, arXiv:2504.18452. doi:10.48550/arXiv.2504.18452
• Weller ZD, Im S, Palacios V, Stuchiner E, von Fischer JC. 2022. Environmental Injustices of Leaks from Urban Natural Gas Distribution Systems: Patterns among and within 13 U.S. Metro Areas. Environmental Science & Technology, 56(12):8599–8609. doi:10.1021/acs.est.2c00097

R package: dlmtree

• Modeled time-varying exposure-response in mixtures using treed DLMs with Bayesian inference for lagged, nonparametric effects.
• Incorporated mixture exposures, heterogeneity, non-linear exposure-time-response effects.
• Developed an R package for efficient implementation of treed DLMs, enabling reproducible analysis, Bayesian diagnostics, and visualization.

Bayesian Inference Hierarchical Modeling Variable Selection MCMC Rcpp Git Package Development HPC Slurm ggplot2 Shiny R Markdown

Urban Natural Gas Leaks and Environmental Injustice

• Developed spatial Bayesian models to estimate leak densities and environmental disparities across 13 U.S. metro areas.
• Integrated methane sensor data, GIS boundaries, and standardized census predictors to perform spatial analyses.
• Produced statistically grounded, policy-relevant insights on how race, income, and housing age shape urban infrastructure risks.

Bayesian Inference Spatial Modeling RStan ggplot2 Mapping Consulting

Invited & Oral Presentations

Posters & Contributed Talks