School of Electronic Engineering and Computer Science

Improving the statistical basis of forensic evidence

Supervisor: Prof Norman Fenton

Research group(s): Risk & Information Management

While DNA evidence has a (peculiarly undeserved) status as being ‘statistically sound’, other types of forensic evidence (Including fingerprints, footprints, shoeprints) do not enjoy such a status. Hence, whereas DNA experts are allowed to attach statistical assertions to the probative value of their evidence (such as ‘random match probabilities) the same is not true of experts in others areas of forensics. The hypothesis of this proposed research is that it is possible to improve the statistical basis for all types of forensic evidence (including DNA) by incorporating expert judgment using Bayesian methods. One of the objectives is to apply the work to provide a sound statistical basis for palynology evidence (this will be done in collaboration with a world-leading palynologist).