I’m an assistant professor of Statistics at the University of British Columbia. I’m also a a core Stan developer and a member of the Centre for AI Decision-Making and Action (CAIDA).
My research primarily focuses on the development and understanding of algorithms that underlie probabilistic programming languages, especially when used for Bayesian modeling and Probabilistic Machine Learning. I’m interested in the application of these methods in several areas, including Public Health, Biomedical Engineering, Ecology and Astrophysics. An outcome of this research is the development of high-performance open-source software, such as Stan, which empower scientists to analyze complex data.
You can find out more by browsing this website or looking at my CV.
News
🦋 Sometimes I post on BlueSky social via @charlesm993.bsky.social.
Old News
August 17th-21st 2026: I attended StanCon in Uppsala, Sweden. In addition to connecting with Stan users and catching up with fellow developers, I gave a talk on the Embedded Laplace Approximation in Stan and presented a poster on Bayesian Synthetic Likelihood for Enhanced Multilevel Network Meta-Regression.
June 28th-July 3rd 2026: I attended the ISBA: World Meeting in Nagoya, Japan. There, I spoke at the session on Principled Tuning of Markov chain Monte Carlo.
June 6th-12th: I participated in the Voyages beyond $\Lambda$-CDM workshop in the Aegan sea in Greece. The workshop brought together a small group of physicists and astrophysicists (and one statistician) on a sailboat to exchange research ideas and have in-depth discussions.
May 29th-30th: I attended the Workshop on Statistical Modeling, Causal Inference, and Social Science in honor of Andrew Gelman’s 60th birthday in New York City.
December 15th-18th 2025: I attended the International Conference on Statistics and Data Science in Sevilla, Spain. There I gave an invited talk on Matching Symmetries with variational inference.
October 2nd 2025: I spoke at the Department of Statistical Sciences’s seminar at the University of Toronto about (once again) Variational inference in the presence of symmetry
September 30th 2025: I spoke the at the Department of Statistics and Actuarial Sciences’ seminar at the University of Waterloo about Variational inference in the presence of symmetry
September 25-27 2025: I attended the Fast and Curious 2: MCMC in action workshop hosted by the University of Toronto. There spoke about Assessing the Convergence of MCMC when running many short chains.
The paper COSMOBENCH: A Multiscale, Multiview, Multitask Cosmology Benchmark for Geometric Deep Learning, led by Ninguyan (Teresa) Huang and with some wonderful collaborators in astrophysics and in machine learning has been accepted for publication at NeurIPS in the dataset & benchmarks track.
My paper with Loucas Pillaud-Vivien and Lawrence Saul, Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs was accepted for publication in the Journal of Machine Learning Research.
(updated August 2026)