Department of Human Genetics
University of Chicago
My academic CV (PDF, 40kB)
I am interested in statistical methods that have small, beautiful ideas, and run perfectly well at large-scale. I work on developing and applying such methods, to solve some data-intensive problems in biology and medicine.
My research interests are in the area of statistical machine learning, primarily method development for real-world predictive modeling tasks:
Hacking data and models with R is fun. I love R's scalability for tackling large-scale computational challenges, and its capability of making elegant data visualizations.
My favorite technology stack: R, Shiny, Docker, D3.js, Python, PostgreSQL