My work focuses on Mathematical Epidemiology, which is an exciting field that draws on various areas of the mathematical sciences. During the COVID-19 pandemic, I have mainly been putting this expertise at the service of the Government, ONS, and NHS, making any statement of other research interests a bit moot. Nevertheless, I am currently particularly interested in efficient statistical inference for these problems, complex data including networks and associated theory, numerical probability, inverse problems, and model simplification.
Most of the support for COVID-19 work comes via the UKRI-funded JUNIPER Consortium.
I am currently funded by the Royal Society Industry scheme IBM Research locally, thinking about how we can make better use of modern computing architectures to solve complex inferential and modelling problems.
I also support development of open-source software for epidemic modelling. My GitHub is here, and amusingly enough I'm old enough to have a SourceForge account. Now there is a great initiative called epirecipes that will hopefully pull together a lot of relevant software.