I’m a senior lecturer in statistics at the University of Bristol.

My current research is on the interface between Bayesian statistics and machine learning.
I am particularly interested in developing approximate inference methods such as approximate Bayesian computation approaches and **variational inference**.
One application is to **likelihood-free inference**, where simulation of data is possible but the likelihood function is unavailable.
Another is to **stochastic differential equations**
I’ve worked on applications to population genetics, physics, ecology and epidemiology.
Another research interest is **experimental design** and how to quickly derive effective high dimensional designs.

- 14 Nov 2019 » Review of ABC talk
- 07 Sep 2019 » High dimensional Bayesian experimental design - part II
- 31 Aug 2019 » High dimensional Bayesian experimental design - part I
- 04 Aug 2019 » Bibtex tips
- 12 May 2019 » Posters in LaTeX
- 28 Apr 2019 » Mailing lists
- 07 Jun 2016 » Bayesian inference by neural networks. Part 2: new paper
- 07 Jun 2016 » Bayesian inference by neural networks. Part 1: background
- 17 Jan 2016 » Jupyter and R basics
- 03 Jan 2016 » Likelihood-free timeline
- 27 Sep 2015 » My work software list
- 20 Sep 2015 » Newcastle staff email on thunderbird