Mathematical Statistics

Enabling the collaborative research in Precision Health that is instrumental in the transition to preventative medicine

John Aston

Physical  Mathematical Statistics  

Prof Aston's research interests include all areas of Applied Statistics but particularly Official and Public Policy Statistics, Statistical Neuroimaging and Statistical Linguistics; and the links between statistics and other areas of pure and applied mathematics. He is also involved in some of Cambridge's AI and COVID-19 work through AIX-COVNET.

public policy statistics  statistical neuroimaging  statistical linguistics  

Sergio Bacallado

Physical  Mathematical Statistics  

Dr Bacallado is a statistician specialising in Bayesian methods and Bayesian nonparametrics. In particular, he has a background in Structural Biology. He develops methods for the analysis of human microbiome studies, and previously worked on applications to molecular dynamics simulations and single-molecule biophysics.

statistics  microbiome studies  molecular dynamics simulations  

Richard Samworth

Physical  Mathematical Statistics  

Prof Samworth's main research interests are in nonparametric and high-dimensional statistics. Particular topics include shape-constrained density estimation and other nonparametric function estimation problems, nonparametric classification, clustering and regression, the bootstrap and high-dimensional variable selection problem. Further applciations include public health, genetics, archaeology and oceanography.

public health  genetics  nonparametric  high-dimensional statistics