Research impact

social media graphics

The Department of Mathematics and Statistics at the University of Reading has a long and established track record of impactful research, working with a wide variety of industrial and academic partners to achieve significant social and economic benefits. We welcome partnership enquiries from commercial and industrial organisations - contact us for an initial project discussion. Our applied research covers a very wide range - from endangered elephants to better weather forecasts - as can be seen from some of our recent case studies below.

Cost-effective clinical trials development

Research into the design and analysis of clinical trials conducted within the Mathematics and Statistics Department of the University of Reading has the potential to cut development and regulatory costs, reduce time-to-market for new treatments, and improve patient outcomes.

Read the full impact case study (pdf file).

Tackling the trade in illegal elephant ivory with modern statistical tools

The Mathematics and Statistics department at the University of Reading has, over many years, developed and improved statistical tools to monitor the world trade in illicit ivory. This work now underpins an international convention on endangered elephants.

Read the full impact case study (pdf file).

Social media - measuring return on investment

Digital communications between individuals have resulted in large, multi-layered social networks that evolve from moment to moment. Although methods exist for analysing and modelling static networks, recent trends in communications, transport and energy have highlighted the need for methods that are appropriate for dynamic, evolving networks.

Read the full impact case study (pdf file).

Improving ocean and climate forecasting

Atmospheric and oceanic forecasting systems require a vast quantity of input data collected from satellites, ocean buoys, aircraft and shipping, radiosondes, radar and ground stations. These data are incorporated into complex multi-scale models using data assimilation techniques. Improvements in such techniques developed at Reading enable better use of this expensively-acquired data to produce more accurate weather and climate predictions.

Read the full impact case study (pdf file).

Extracting maximum value from input observations in weather forecasting models

Effective and timely use of observational data is vital for forecasting any environmental system, and particularly so for weather forecasting because of the chaotic nature of the atmosphere. Research undertaken within the Mathematics and Statistics Department has led to better treatment of particular types of observational data in numerical weather prediction, resulting in significant improvements in operational analysis and forecast skill.

Read the full impact case study (pdf file).

Efficient simulation of fluid flow in oil or gas reservoirs

The more accurately fluid flow in a potential oil field can be assessed, the more efficiently and economically it can be developed, but the problem is an extremely complex one with many variables. Work undertaken at the University of Reading's Department of Mathematics and Statistics, working with Schlumberger PLC, developed a tool to provide fast, robust and efficient simulation of fluid flow in reservoirs.

Read the full impact case study (pdf file). 

For more information on our research please visit our research groups page, contact us on +44 (0) 118 378 8996, or e-mail

Things to do now

Contact us

Page navigation


Search Form

A-Z lists