I develop statistical methods for causal discovery and algorithmic fairness. I've applied these methods to quantify racial bias in peer review and ballot order bias in election administration. In addition, I have worked in computational algebraic geometry (see publications sidebar), MCMC sampling algorithms (undergraduate thesis), machine learning in genomics (internship at Microsoft Research), and medicine (UW statistical consulting program).
If you're looking for code samples:
Open Science Foundation repository for NIH peer review data and Erosheva et al. (2020) reproduction code