Research Topics
Problem solving in mathematics and statistics is inspiring and enjoyable, but are achievements in mathematics and statistics any use in the socalled 'real world'?
The work of mathematicians and statisticians often turns out useful and essential, but typically in a less concrete manner than say the work of a scientists or a physician. David Hilbert, in his now historical address to scientists and physicians, put it this way:
"The instrument that mediates between theory and practice, between thought and observation, is mathematics; it builds the connecting bridge and makes it stronger and stronger. Thus it happens that our entire presentday culture, insofar as it rests on intellectual insight into and harnessing of nature, is founded on mathematics"
Almost a century after Hilbert's words, the mathematical fundations of sciences and social sciences, and the evidence based approach in medicine are often being taken for granted. In the 21st century we are facing complex big data sets with unknown structures and and ongoing discourses about objective and subjective notions of risk and uncertainty.
Probability and statistics are mathematical disciplines for modelling and analysing theoretical and practical questions arising from this.
Researchers in Statistics at Warwick are developing and utilizing modern statistics, mathematics and computing to solve practical problems such as:
 Discovering which genes can discriminate between diseased and healthy patients
 Modelling and detecting asset price bubbles while they are happening and before they burst
 Modelling infectious diseases and identifying localized outbreaks
 Developing a fast algorithm through probabilistic modeling for compression of sound data
 Automatically diagnosing diseases with largescale image data Utilizing crime data for crime prevention and optimal allocation of police resources
 Predicting the outcome of elections based on exit poll data
 Computed Tomography validation of complex structures in Additive Layer Manufacturing

Probability of containment for multitype branching process models for emerging epidemics

Nonstationary statistical modeling and inference for circadian oscillations for research in cancer chronotherapy

Bayesian Models of CategorySpecific Emotional Brain Responses

Decision focused inference on Networked Proabilistic Systems: with applications to food security

Rotationally invariant statistics for examining the evidence from the pores in fingerprints

Dynamic Uncertainty Handling for Coherent Decision Making in Nuclear Emergency Response

Study of Key Interventions into Terrorism using Bayesian Networks

Assessing the risk of subsequent tonicclonic seizures in patients with a history of simple or complex partial seizures

Multidimensional Markovfunctional Interest Rate Models

Prospect Theory, Liquidation and the Disposition Effect

Dynamic BradleyTerry modelling of sports tournaments