Chris Sherlock’s Home Page
Home - Publications - Supervision - Teaching
Welcome
I am a Professor of Statistics within the Mathematics and Statistics department at Lancaster University. On these pages you will find information about my research publications and supervision, teaching and other professional activities.
Contact: c (dot) sherlock (at) lancaster (dot) ac (dot) uk
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Research
My research interests include:
Markov chain Monte Carlo (MCMC):
theory on convergence and efficiency of MCMC algorithms;
methodology such as pseudo-marginal MCMC and non-reversible MCMC;
application of MCMC, especially in areas such as systems biology, epidemiology, ecology and the environment;
Particle filters and Sequential Monte Carlo, especially their use within MCMC algorithms;
Inference for Markov jump process and diffusion models in systems biology and ecology, in particular developing new bridges for use in particle MCMC algorithms;
More general statistical inference for ecology, epidemiology and the environment.
Research-level tutorials
Pseudo-marginal MCMC opened up inference for SDEs and MJPs to a relatively standard approach using particle filters. Here is a simple explanation of the basics and (partial) review of the literature.
Variational representations of Markov kernels can be powerful tools in the analysis of their behaviour; here is a description of three that I have found useful.
During my PhD I found out a little about - particle filters; here is an introduction to the SIR and ASIR filters - an explanation for beginners.
Admin
I am (2019-present) the group lead for the Computational Statistics group and extensions and (2024-) head of curriculum development for the MARS (Mathematics for AI and Real-world Systems) UG programme. Between 2022-23 I was dissertation co-ordinator for the MSc in Statistics. From 2013-2019 I was the Programme Tutor for the MSc in Statistics. From 2007-2013 I was Admissions Tutor for the MSc in Statistics.