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

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!

Statistics Office Hours Livestream (YouTube)
Patreon Livestream (August 2022)

Statistics Office Hours Livestream (YouTube)
Patreon Livestream (April 2022)

Autodiff for Implicit Functions Paper Livestream (YouTube)
Patreon Livestream (December 2021)

Statistics Office Hours Livestream (YouTube)
Patreon Livestream (October 2021)

Question and Answer Livestream (YouTube)
Patreon Livestream (August 2021)

Bayes Factor Workflow Paper Livestream (YouTube)
Patreon Livestream (March 2021)

Visualization Question and Answer Livestream (YouTube)
Patreon Livestream (May 2020)

Question and Answer Livestream (YouTube)
Patreon Livestream (April 2020)

Question and Answer Livestream (YouTube)
Patreon Livestream (March 2020)

Episode 6: A principled Bayesian workflow (Learning Bayesian Statistics)
Learning Bayesian Statistics (January 2020)

Markov Chain Monte Carlo Part 3 (VideoKen)
London Machine Learning Summer School 2019 (July 2019)

Markov Chain Monte Carlo Part 2 (VideoKen)
London Machine Learning Summer School 2019 (July 2019)

Markov Chain Monte Carlo Part 1 (VideoKen)
London Machine Learning Summer School 2019 (July 2019)

Scalable Bayesian Inference with Hamiltonian Monte Carlo (YouTube)
Michigan Institute for Data Science (MIDAS) Seminar Series (March 2019)

Scalable Bayesian Inference with Hamiltonian Monte Carlo (YouTube)
Data Science Sydney (February 2019)

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)