About me

My core research is in computational statistics. I develop and analyse algorithms for Bayesian inference, including sequential Monte Carlo and Markov chain Monte Carlo. I work with applied scientists to develop principled and robust data analysis for their data. Often this involves designing Bayesian models to incorporate domain and expert knowledge. I also design open source software for statisticians, scientists and industry.

Since September 2023, I am a postdoctoral researcher supervised by Professor Christian Robert at Université Paris-Dauphine, Paris Sciences & Lettres. I am working on principled Bayesian inference algorithms with data privacy guarantees. In pursuit of this goal we are developing a framework for defining privacy guarantees for use in scientific, industrial and other contexts with differing privacy requirements.

In Paris I co-organise the Mostly Monte Carlo Seminar Series. In 2023 I was chair of the committe organising SMC Down Under.

Current projects

  • A Bayesian decision-theoretic framework for statistical data privacy
  • Monte Carlo twisted particle filters arXiv
  • Calibrating surrogates models for intractable Bayesian posteriors arXiv
  • Particle filters for binary state spaces
  • Tidy software for BART causal treatment effect models R package

Selected Journal articles

See Google Scholar for more details.