Speaking

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.

Upcoming Talks

Master Class: Toward a Principled Bayesian Workflow
Thursday, October 18, 2:40 PM–3:20 PM
PyData NYC

Scalable Bayesian Inference with Hamiltonian Monte Carlo
Friday, November 2, 4 PM–5 PM
Biodiversity Legendary Internal Seminar Series
Beaty Museum Auditorium
University of British Columbia

Recorded Appearances

Occasionally my talks are recorded and made available online. As the understanding of the material is rapidly evolving the most recent talks are highly recommended over older talks covering the same material. If you know of any talks that I am missing here then please let me know!

Scalable Bayesian Inference with Hamiltonian Monte Carlo (YouTube)
London Machine Learning Meetup (June 2018)

Robust Data Science with Statistical Modeling (DataCamp)
DataFramed Podcast (May 2018)

Statistical Pitfalls – Coincidences (~15:40) (DataCamp)
DataFramed Podcast (April 2018)

Statistical Pitfalls – Best Fits (~37:20) (DataCamp)
DataFramed Podcast (April 2018)

Statistical Pitfalls – Concentration of Measure (40:37) (DataCamp)
DataFramed Podcast (January 2018)

Statistical Pitfalls – Selection Bias (19:24) (DataCamp)
DataFramed Podcast (January 2018)

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)