A once and future physicist masquerading as a statistician, I work on general purpose tools that allow
scientists to maximize the utility of their data (i.e. Bayesian inference).
This pursuit has lead me to the application of differential geometry to Markov Chain Monte Carlo
techniques via the Hamiltonian Monte Carlo. Along with some talented colleagues I am developing both
the theoretical foundations and practical implementations of the algorithm, the latter particularly
Outside of scientific pursuits I've been known to take food and spirits a little too seriously.