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MA (Oxon), MSc (Manchester), PhD (Liverpool), FIMA, FHEA.

Following research and teaching in Mathematics, he was appointed Dean of Research in September 2008 and became Pro-Vice-Chancellor (Research and Knowledge Transfer) in 2015. For many years he has led the University’s Mathematical Sciences Research Group, becoming Professor of Computational Applied Mathematics in 2000. He was elected to an invited Fellowship of the Institute of Mathematics and its Applications in 2007 for his personal contribution to the advancement of Mathematics. Within his current role as Pro-Vice-Chancellor for Enhancement on a fractional basis, Neville is part of the HEFCE TRAC Development Group and is also on a national group looking at the financial sustainability of alternative modes of HE provision. He has responsibility for the University's work on Apprenticeships and has oversight of the various data returns made by the University each year.

A former member of the Engineering and Physical Sciences Research Council peer review College, an Expert Advisor to the European Commission on the Framework 7 and Horizon 2020 Programmes and having held three Leverhulme Trust grants, Neville continues to be an active researcher in Mathematics. His work in fractional and delay differential equations is highly regarded internationally and he is part of the COST Network 'Fractional'. He is an Editor for some of the leading journals in the field, SIAM journal on Scientific Computing, the Journal of Integral Equations and Applications, Applied Numerical Mathematics and Fractional Calculus and Applied Analysis.

Neville’s academic interests focus on modelling and simulation.  Modelling and simulation of real-life problems is important to scientists and engineers for a wide variety of reasons: experimentation may be too costly, too dangerous or simply take too long and so the alternative of having some form of computer model to predict the outcome of experiments is very attractive. However the model is only useful if its results correctly mimic those of the real world problem that it attempts to simulate and therefore the quality assurance of computational models is a key area of research.

In the work of our research group, we investigate the reliability of computer simulations of problems in engineering, the biosciences and the environmental sciences which are characterised by the presence of a time-lag, a memory or a delay. For example, in materials science, the way in which a material behaves depends on the historical stresses and strains it has experienced - it has a memory!  Similarly, as the body builds a resistance to drug therapy, again we recognise a memory effect. Delays are present in many controls, for example in the knob that controls the temperature of a shower, or in the time it takes for medical staff to recognise a change in condition and intervene with a new treatment. We aim to develop simulations that are reliable (they reflect accurately the underlying world that they simulate), efficient (they require the minimum resource to run, and produce an answer in reasonable time) and stable (so they are not much affected by poor quality data.