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Durham University

Department of Mathematical Sciences

Research Excellence Framework 2014

Department of Mathematical Sciences Results

84% of our Unit of Assessment's research overall is considered of internationally excellent quality or world leading, that is, both 3* and 4*. This consists of the overall assessment of outputs, environment and impact. This gives our Unit of Assessment a Grade Point Average (GPA) of 3.06. This data is from the Higher Education Funding Council for England (HEFCE).

We are particularly proud of the fact that all full-time staff were returned for this exercise, and that Durham Mathematical Sciences comes in seventh position in the Higher Education Statistics Agency (HESA) intensity ranking of the 53 Departments of Mathematics assessed, behind Cambridge, Oxford, Imperial College, Bristol, Dundee and Warwick.

Equally satisfying is our 6th position in the national ranking for impact, based on GPA. We are joint first on the percentage of 3* and 4* for impact (100%), and also joint first on the percentage of 3* and 4* for environment (100%).


Research Impact - Benefits of our Research

Industry, the environment and healthcare have benefited from statistical methods for making predictions from complex and uncertain data. Professor Michael Goldstein, Professor David Wooff and Dr Peter Craig, of the Department of Mathematical Sciences at Durham University, collaborated on developing statistical methodology for a range of applications including:

  • Making predictions about oil and gas reserves, helping exploration companies to plan and manage their drilling operations more efficiently.
  • Predicting demand for out-of-hours urgent health care in the UK, resulting in greater efficiency and cost savings.
  • Long-range climate projections in the UK that have influenced investment decisions in sectors as diverse as flood defence, transport, energy supply and tourism.
  • Efficient maintenance schedules for stations, bridges and other structures on the London Underground.
  • Risk assessment for allergic skin reactions from products made by two multinational companies.
  • Optimising ‘pay per click’ online advertising, helping a UK digital marketing company win clients and strengthen its market position.
  • Predicting patterns of bicycle use in towns, helping to inform the UK Government’s programme to encourage cycling.
  • Assessment of variation in sensitivity of living creatures to pesticides used in food production, which has informed the European Union’s policy on managing ecotoxicological risk.

The collaborative research projects above were selected as one of six winners of Durham University’s Award for Excellence in Research Impact in 2014.

Impact Case Studies

Based on original research by Peter Craig, several risk assessment methods, published in EFSA (European Food Safety Authority) 2005 Scientific Opinion on the “possibility of lowering the uncertainty factor ...”, have been applied, or agreed as policy, in further official documents concerning risk assessment for aquatic species. The documents, from EFSA and national authorities, e.g. Sweden, are: (i) official EU risk assessments for specific chemicals and (ii) creation of EU and national policy through official guidance for risk assessments. Supported by further research by Peter Craig, the methodology was recommended by the 2008/9 EFSA guidance on risk assessment for birds and mammals for application in that wider context. Through changes to risk assessment guidelines and practice, the research has changed the management of the ecotoxicological aspect of environmental risk in the EU.

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ENABLE is a history matching and uncertainty assessment software system for the oil industry, whose inference engine was produced by the Durham Statistics group, based on their research on uncertainty quantification for complex physical systems modelled by computer simulators. The system optimizes asset management plans by careful uncertainty quantification and reduces development costs by accelerating the history matching process for oil reservoirs, resulting in more informed technical and economic decision-making.

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This study demonstrates how Bayes linear methodologies developed at Durham University have impacted on industrial practice. Two examples are given. The approach has been applied by London Underground Ltd. to the management of bridges, stations and other civil engineering assets, enabling a whole-life strategic approach to maintenance and renewal to reduce costs and increase safety. The approach has won a major award for innovation in engineering and technology. The methodology has also been applied by Unilever and Fera to improve methods of assessing product safety and in particular the risk of chemical ingredients in products causing allergic skin reactions.

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The Climate Change Act, 2008, constructed a legally-binding long-term framework for the UK to cut greenhouse gas emissions and a framework for building the UK’s ability to adapt to a changing climate. The Act requires a UK-wide climate change risk assessment (CCRA) that must take place every five years and a national adaptation programme (NAP), setting out the Government’s objectives, proposals and policies for responding to the risks identified in the CCRA. The CCRA, and thus the NAP, drew heavily on the uncertainty analysis for future climate outcomes, published in 2009 by the Met Office as the UK Climate Projections UKCP09, which in turn drew heavily on research into the Bayesian analysis of uncertainty for physical systems modelled by computer simulators carried out at Durham University. A wide range of industries and public sector organisations likely to be affected by climate change have consulted with the Met Office on UKCP09 to inform decisions on policy and investment, involving billions of pounds, in sectors as diverse as flood defence, transport, energy supply and tourism.

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The Northern Doctors Urgent Care Group, a not-for-profit organisation that delivers out-of-hours urgent medical services for the NHS, achieved significant efficiency savings and improvements in-patient care as a result of adopting statistical assessment and forecasting processes, developed by Durham University. In addition, the Durham methodology was adapted to assess the results of a Government programme to encourage cycling in six UK towns, producing data on cycle use that helped to influence subsequent allocations of about £700M for sustainable transport projects.

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This work revolutionizes the way in which pay-per-click (PPC, internet search) advertising is optimised. Recent estimates suggest that 80% of companies market online, yielding $30 billion of revenue to companies managing the process. The research of the Durham team gives a collaborating company, Summit Media Ltd, a substantial lead in statistical tools to provide PPC optimisation.

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