I’m an assistant professor of Statistics at the University of British Columbia. I’m also a member of the Centre for AI Decision-Making and Action (CAIDA) and a core Stan developer.
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.
- June 28th - July 3rd 2026: I will attend the ISBA: World Meeting in Nagoya, Japan. There, I will speak at the session on Principled Tuning of Markov chain Monte Carlo.
Old News
Applications for UBC graduate programs in Statistics are now open! The deadline for the PhD program is December 1st.
December 15th-18th 2025: I attendws 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.
August 26-27 2025: I attended the CANSSI Monte Carlo workshop at UBC. There I’ll give a talk on Assessing the Convergence of MCMC when running many short chains.
June 29 - July 06 2025: I taught at the summer school on cryptography, statistics and machine learning in Tsaghkadzor, Armenia. My course: Bayesian Statistics: a practical introduction. [slides].
June 16-20 2025: I attended BayesComp in Singapore to chair a session on Parallel Computation for Markov chain Monte Carlo, and gave an invited talk at the session on Advances in Variational Inference.
May 3-5 2025: Lawrence Saul and I received the best paper award at AISTATS 2025 for our paper on Variational Inference in Location-Scale Families.
I accepted a position as an assistant professor of statistics at UBC: here’s a short statement.
(updated January 2026)