Reading group and group meeting

We meet weekly for a Bayesian computation reading group to discuss recent and classic papers, and also for a group meeting at which we discuss our current research.

Current group members

Ivis Kerama is a PhD student funded by the EPSRC Mathematics of Planet Earth CDT and Cefas. He is working on "Improved Approximate Bayesian Computation for inference of the likely effects of climate change on animal populations”, co-supervised by Richard Sibly and Robert Thorpe. This project is part of an initiative on Individual-Based Modelling at the University of Reading.

Laura Mansfield is a PhD student funded by the EPSRC Mathematics of Planet Earth CDT. She is working on "Model reduction using emulation for understanding and predicting climate responses to different regional emission forcing”, co-supervised by Brian Hoskins and Apostolos Voulgarakis. Laura has a twitter account.

Leonardo Ripoli is a PhD student funded by the EPSRC Mathematics of Planet Earth CDT. He is working on "Climate Change and Infectious Diseases", co-supervised by Andrew Meade and Oliver Ratmann.

Previous group members

Felipe Medina Aguayo was a postdoc on my BBSRC project “Understanding recombination through tractable statistical analysis of whole genome sequences”. He worked on applying recently developed techniques in Bayesian computation to whole genome sequence data, and on developing his own Bayesian computation methodology. Felipe is now a Postdoctoral Researcher at CIMAT (Centro de Investigación en Matemáticas) in Guanajuato, Mexico.

Philip Maybank was an EPSRC PhD student working on statistical methods for neuroscience, whose thesis was entitled "Bayesian inference for stable differential equation models with applications to computational neuroscience". He focussed on new methods for parameter estimation for differential equation models of brain activity from EEG data, in collaboration with Ingo Bojak. Philip is blogging about his research here. He is now working at the Numerical Algorithms Group in Oxford. Philip has a linkedin account.

Richard Culliford was a PhD student, funded by the University of Reading and the Modernising Medical Microbiology consortium at the University of Oxford, whose thesis was entitled "A Sequential Monte Carlo Algorithm with Transformations for Bayesian model exploration: Applications in Population Genetics". He worked on sequential Monte Carlo for online Bayesian inference for the coalescent, and for Bayesian model comparison, collaborating with Daniel Wilson. Richard has a linkedin account.

Mark Bell was a postdoc on my EPSRC project "Tractable inference for statistical network models with local dependence”. He worked on improving Bayesian inference techniques for statistical models for networks. On leaving my group, Mark took up a post as Senior Statistician at the Transport Research Laboratory. Mark has has a linkedin account.

Changqiong Wang was an EPSRC PhD student whose thesis was entitled "Applications of Monte Carlo methods in studying polymer dynamics”. She used Bayesian statistics to fit statistical models to molecular dynamics data, and was co-supervised by Zuowei Wang and Patrick Ilg. Changqiong's research project was instigated by the brilliant physicist Alexei Likhtman, who tragically died several years ago. After finishing her PhD, Changqiong took up a post as Research Assistant in Data Science in the School of Agriculture Policy and Development at Reading, followed by working as a postdoc at Queen Mary University of London. Changqiong has a linkedin account.

Other projects

In recent years I have focussed on developing the methodology of sequential Monte Carlo (SMC) and approximate Bayesian computation (ABC), motivated by applications in several fields. Particular focuses have been

  • Bayesian inference for doubly intractable distributions, i.e. distributions with an intractable partition function such as Markov random field models (including exponential random graph models (ERGMs)).
  • "Noisy" Monte Carlo methods, which approximate exact methods.
  • Bayesian model comparison.

I was formerly a postdoc on the Modernising Medical Microbiology project at the University of Oxford, and before that a Brunel Fellow in Statistics under the SuSTaIn programme in the Department of Mathematics at the University of Bristol (where I also studied for my PhD under the supervision of Peter Green). Prior to this I was a researcher at QinetiQ, specialising in target tracking, signal and image processing and classification.

Links to all of my publications, and to my PhD thesis, can be found on my Google Scholar profile.