Eric A. Dunipace
Psychiatry · Biostatistics · Causal inference · Optimal transport
I’m a fourth-year psychiatry resident at UCLA, with a PhD in biostatistics from Harvard. My research focuses on developing statistical methods for causal inference, particularly optimal transport, and building statistical software. Outside of research, I co-founded TraumaLink, an emergency response system in Bangladesh, and helped secure a $150,000 USAID grant for it. I also enjoy teaching and have mentored students in biostatistics and data science. More details are in the tabs above.
selected work
- Paper · 2025Interpretable model summaries using the Wasserstein distance The American Statistician
Summarizes large models with a chosen budget of parameters while staying close, in Wasserstein distance, to the full model.
- PreprintOptimal transport weights for causal inference arXiv:2109.01991
Causal weighting that targets distributional balance by minimizing optimal transport distances between treatment and control groups.
- R packageWpProj
Wasserstein projections for interpretable model summaries, available on CRAN.
- R packageRcppCGAL
Brings the CGAL computational geometry library's C++ headers to R through Rcpp.
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