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Associate Professor in Statistics, Durham University

My main research interests are in Bayesian approaches to modelling and uncertainty quantification. I am mostly interested in the development and implementation of models and the design of emulators (statistical representations) for large complex systems such as health, climate, and population dynamics. My current research is focused on multi-model uncertainty looking at frameworks for assimilating multiple models and experts’ beliefs, the aim of these frameworks is to unify multiple uncertainty specifications and provide an accessible decision support mechanism. This approach is essential when studying systems such as health where fast and reliable tools are necessary to aid decision making or such as climate where different modeling approaches are used by experts in different areas to inform policy makers. My current collaborations involve the development of Bayesian methods and their application to a number of areas including health, engineering, societal dynamics, climate, seismology, and banking. Most of these partnerships are generating substantial outputs with current and eminent impact in the local industry and society.

Experience

  • –present
    Associate Professor in Statistics, Durham University

Education

  • 2011 
    Durham University, PhD in Statistics