Matthew Sutton completed his PhD in 2019 developing new statistical methods to analyse high dimensional data from clinical heath and biological problems. He worked as a postdoc at Lancaster University as part of the multi-university Bayes4Health grant in the United Kingdom.
His research interests span broadly across Monte Carlo methods, high dimensional statistics and Bayesian methodology. A particular focus of his current research is in the development of continuous-time Monte Carlo methods for speeding up the computation required for Bayesian inference. He is a currently working on the Models and Algorithms research program for the centre.