15 May 2013

Head of ACSE collects prestigious award for ground breaking paper

Professor Visakan KadirkamanathanProfessor Visakan Kadirkamanathan, Head of Automatic Control & Systems Engineering and a member of the Centre for Signal Processing and Complex Systems, recently flew to Washington DC to receive an award which was announced at the US National Academy of Sciences for his work on his 'Afghan War Diary' paper. The paper helped to create models that accurately predict the future of military conflicts.

Chosen from more than 3,700 research articles in one of the world's most-cited multidisciplinary scientific journals, Professor Kadirkamanathan, along with his colleagues from the universities of Edinburgh and Columbia collected the Cozzarelli Prize, an award which recognises outstanding contributions to scientific excellence and originality.  The work was carried out via a University of Sheffield Endowed Scholarship and all four authors were originally based in Sheffield.

Titled ‘Point process modelling of the Afghan War Diary’ the paper is based on classified information revealed by whistleblower website Wikileaks about the Afghan war. The team of scientists were able to predict armed opposition group activity way into the future of the battle. This was achieved by using war logs with about 77,000 events including location, day and time of occurrence and other details from the war in Afghanistan between 2004 and 2009.

 “Models of conflict dynamics provide a key advantage in their ability to predict and forecast how the conflicts escalate over time, an important source of information for decision making” said Professor Kadirkamanathan, “In our study, the statistical models used can also provide a measure of the uncertainty associated with the predictions, and not just the prediction of the level of the conflict.”

 “Conflict dynamics models of the type developed here can provide forecasts of the levels of conflict with a degree of uncertainty, and reveal geographically spatial patterns in the conflict. The model was able to show in map form the growth in the intensity of the conflict during the period of 2004-2009 as well as its volatility. Independent from the data used in the models, we were able to predict the armed opposition group activity in 2010.”

The new technology could be used in the future to help better plan deployment of resources, including soldiers, and better manage conflicts.  The results of the project have been published by the Proceedings of the National Academy of Sciences and are part of a growing movement to understand and predict episodes of political and military conflict using data driven modelling techniques.

The development of spatio-temporal modelling techniques, such as the one used in this study, are being pioneered within the University of Sheffield’s Centre for Signal Processing and Complex Systems.

Please see the PNAS news release for further information about the award.

To view the award winning paper online please see: AbstractFull paper