Department of Statistical Science

Statistical Science

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Computational Statistics

Theme Overview

This theme is concerned with advancing the theory, methodology, algorithmic development and application of simulation based approaches, such as Markov Chain Monte Carlo, to statistical inference.

Theme Members

Name	Position	Selected Applications	Keywords
Mark Girolami	Professor (Theme Lead)
Alexandros Beskos	Lecturer
Maria De Iorio	Reader
Tom Fearn	Professor	Near infrared spectroscopy	Multivariate analysis, calibration, classification, Bayesian methods
Serge Guillas	Reader
Christian Henning	Senior Lecturer	Various, currently including biogeography, musicology	Cluster analysis, multivariate data analysis and robust methods
Ioannis Kosmidis	Lecturer
Ricardo Silva	Lecturer
Trevor Sweeting	Professor	Various, currently biological and medical applications, information retrieval systems	Bayesian theory, predictive inference, hybrid Bayesian computation, Dirichlet process mixture models
Jinghao Xue	Lecturer

Recent Grants

• Inference-based Modelling in Population and Systems Biology - BBSRC BB/G006997/1 - 2010 to 2013
• The Silicon Trypanasome - BBSRC - 2011 to 2014
• Computational Statistics and Cognitive Neuroscience - EPSRC EP/H024875/1 - 2009 - 2011
• Advancing Machine Learning Methodology for New Classes of Prediction Problems - EPSRC EP/F009429/1 - 2007 - 2011
• The Molecular Nose - EPSRC EP/E032745/1 2007 to 2011
• The Synthesis of Probabilistic Prediction and Mechanistic Modelling within a Systems Biology Context - EPSRC EP/E052029/1 - 2007 to 2012
• Key Survival Pathways in CML Stem Cells and Novel Approaches to their Eradication - CRUK - 2010 to 2015
• Analysing and Stryking the Sensitivities of Embryonal Tumours - EU FP7 - 2011 to 2015
• Bayesian Inference in Systems Biology: Modelling Organ Specificity of Circadian Control in Plants - Microsoft Research - 2007 to 2011
• Developments of Multiple Kernel Methods for Produce Recognition - NCR Laboratories - 2011 to 2012
• A Population Approach to Ubicomp System Design - EPSRC EP/J007617/1 - 2011 to 2016
• Sequential Monte Carlo methods for applications in high dimensions - EPSRC EP/J01365X/1 - 2012 to 2013
• Learning Highly Structured Sparse Latent Variable Models - EPSRC EP/J013293/1 - 2012 to 2013
• Advancing the Geometric Framework for Computational Statistics: Theory, Methodology and Modern Day Applications - EPSRC EP/J016934/1 - 2012 to 2017