Throughout my undergraduate and graduate education in experimental physics I long struggled with a poor understanding of statistics. Consequently I am now passionate about improving statistics pedagogy and communication, especially for early-career researchers. As opportunity permits I travel around the world speaking about statistical workflow and computation as well as hosting intensive, interactive Stan workshops. If you are interested in having me speak or host a workshop then please don’t hesitate to contact me. I am particularly interested in hosting workshops for underrepresented communities and minority-serving institutions.

Occasionally my talks are recorded and made available online. If you know of any talks that I am missing here then please let me know!

Scalable Bayesian Inference with Hamiltonian Monte Carlo (ICERM Video Archive)
ICERM Workshop on Stochastic numerical algorithms, multiscale modeling and high-dimensional data analytics (July 2016)

Some Bayesian Modeling Techniques in Stan (YouTube)
Tokyo Stan Meetup (June 2016)

Scalable Bayesian Inference with Hamiltonian Monte Carlo (YouTube)
Tokyo Stan Meetup (June 2016)

The Geometrical Foundations of Hamiltonian Monte Carlo (YouTube)
NIPS 2014 Workshop on Riemannian Geometry in Machine Learning, Statistics, and Computer Vision (December 2014)

Hamiltonian Monte Carlo and Stan (Part 2) (YouTube)
Machine Learning Summer School, Iceland 2014 (April 2014)

Efficient Bayesian inference with Hamiltonian Monte Carlo (Part 1) (YouTube)
Machine Learning Summer School, Iceland 2014 (April 2014)

A General Metric for Riemannian Hamiltonian Monte Carlo (YouTube)
Geometric Science of Information 2013 (August 2013)

Cruising the Simplex: Sampling the Dirichlet Distribution with Hamiltonian Monte Carlo (YouTube)
31st International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (July 2011)