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I tend to divide my research time equally between doing mathematics with a pencil and paper, testing ideas numerically by doing some programming, and learning about different application areas.  The below summarises my current interests.​​

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Bayesian Computation

This is my primary field of research.  I have dedicated a lot of my research to better understanding some Markov chain Monte Carlo algorithms (MCMC), such as:

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• Hamiltonian (HMC) and Langevin (MALA, ULA) Monte Carlo

• Non-reversible Markov processes and MCMC methods

• Intelligent MCMC on discrete state spaces (for e.g. variable selection)

• Pre-conditioning & Adaptive MCMC

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Recently a colleague and I developed a new gradient-based algorithm called The Barker Proposal. You can read more about it on my publications page.

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Health Data Science

I work across application areas within health and biology. Some past/current projects are:

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• Inference and model selection for survival data in health economics

• Analysis and modelling of human microbiome data

• Modelling demand for children's ambulances services (in collaboration with Great Ormond Street hospital and UCL Clinical Operational Research Unit)

• Modelling Rate of Oxygen efficiency in mechanically-ventilated ICU patients (together with Great Ormond Street hospital)

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