Dr. Banet's lab studies the long term effects of increased stress in juvenile fish and, separately, the predation on juvenile salmon by non-native species. I help the Banet Lab with some of their statistical analyses regarding these research topics.
Stan is software targeting Bayesian statistics and, more generally, high-performance statistical computing. The core development team is a friendly and active group of computer programmers turned statisticians -- or is it the other way around? Contributing to the Stan code base is great fun and a terrific way to learn/practice programming. I like to think about the Hamiltonian Monte Carlo algorithm behind Stan.
I'm currently developing a general MCMC sampling library, written in Julia, for Bayesian statistics MCBayes.jl.
Recently, I worked with Bob Carpenter and Brian Ward to develop BridgeStan.
A little while ago, I played around with rewriting parts of Stan's internals, and wrote up a technical report despite my failed attempts to make the software faster for all models of interest.
If not working on Stan, then I'm most likely working on my interactive lecture notes on basic statistics topics. This project is still pretty young, but I've finally nailed down the software I'll use. The interactive webpages depend on a combination of Svelte, Svelte Kit, Plotly.js, Bootstrap, and some elbow grease. The start to these lecture notes is hosted at Lecture Notes, but this will change, in a number of ways, within the next year or so. Stay tuned.