I am a Professor of Statistics in the Department of Mathematics and Statistics at Lancaster University.
I am interested in problems pertaining to Bayesian machine learning and computational statistics, with a focus on Markov chain Monte Carlo and sequential Monte Carlo techniques. My current research is focused on Bayesian methods for large-scale datasets and tools for online learning. I have also worked on problems related to Gaussian processes and network modelling.
I currently hold a UKRI-EPSRC Turing AI Fellowship on Probabilistic Algorithms for Scalable and Computable Approaches to Learning (PASCAL) and formerly an EPSRC Innovation Fellowship on Scalable and Exact Data Science for Security and Location-based Data. I am also a Co-I on the EPSRC-funded Data Science for the Natural Environment and the NERC-funded Signals in the Soil project.
I am the Chair of the Royal Statistical Society Section on Computational Statistics and Machine Learning RSS-CSML and also a member of the EPSRC Mathematical Sciences Early Career Forum. I am currently an Associate Editor for the journal Data-Centric Engineering.
PhD in Statistics and Operational Research, 2014
Lancaster University
MRes in Statistics and Operational Research, 2011
Lancaster University
BSc in Mathematics, 2006
University of Manchester
Apr 18 - Apr 24
Dec 19 - Nov 20
A Python package based on JAX for stochastic gradient Monte Carlo sampling.
A nonparametric Bayes package for the Julia language.
An R package based on Tensorflow for stochastic gradient Monte Carlo sampling.
Postdoctoral Research Associates:
PhD Students: