Research
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.
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
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Non-reversible Markov processes and MCMC methods
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Intelligent MCMC on discrete state spaces (for e.g. variable selection)
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Pre-conditioning & Adaptive MCMC
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.
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
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Analysis and modelling of human microbiome data
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Modelling demand for children's ambulances services (in collaboration with Great Ormond Street hospital and UCL Clinical Operational Research Unit)
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Modelling Rate of Oxygen efficiency in mechanically-ventilated ICU patients (together with Great Ormond Street hospital)
I am looking to expand into different application areas within health and beyond, so feel free to get in touch if you have an exciting modelling problem.