I am a statistician by training, and I am particularly interested in developing and applying causal inference methods in ecology and conservation. In these domains, causal inference methods are often complicated by the fact that a unit’s potential outcomes may depend on the exposure of other units. This is known as causal inference with interference.
I maintain several R packages, including
geex, a package which (hopefully) makes programming estimating equations easier. I created
geex from a pragmatic need to quickly iterate and debug variance estimation from a set of estimating equations. Without knowing its name at the time, the crucial abstraction I used in
geex is a common technique called currying. The way I was able to align mathematical reasoning with computer programming led down the path of functional programming (and once I discovered Haskell, category theory).
See my google scholar profile.
- Causal inference
- Research software design and engineering
- Applied Category Theory
- DrPH Biostatistics, University of North Carolina, 2017
- MS Biostatistics, University of North Carolina, 2015
- AB English, University of Georgia, 2000