Social and Guest Lecture

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Queen Mary University of London

Mile End Road

London

E1 4NS

United Kingdom

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Celebrate the launch of the new MSc Degree Apprenticeship Programme in Data Analytics and welcome the first cohort of apprentices to QM.

About this Event

A warm welcome is extended to all Masters students from the School of Electronic Engineering and Computer Science to a welcome event for the 2019-2021 cohort of MSc Degree Apprentices from the BBC, British Airways, Tata Consultancy, IBM and CGI.

The event will start with refreshments from 4pm in the Engineering Building Foyer followed by a guest lecture by Norman Fenton, Professor in Risk Information Management, from 5pm-5.45pm in PP2 Lecture Theatre.

Guest Lecture by Norman Fenton, Professor in Risk Information Management, School of Electronic Engineering and Computer Science at Queen Mary University of London.

Title: Bayes and the Law: How much can we trust DNA evidence?

Abstract: Suppose that DNA ‘matching’ a suspect is found at a crime scene. A forensic expert asserts: “It is a million times more likely to obtain these DNA results if the DNA comes from the suspect than if it did not”. How convinced should you be that the DNA does comes from the suspect? This talk will show that the answer is often not what most people believe. When used properly probability and statistics (especially Bayesian probability) can help understand the probative value of forensic (and other) evidence and also reveal fundamental errors of reasoning committed by both forensic experts and lawyers. However, where probability and statistics have been explicitly used in court, more often than not their presentation, reasoning and interpretation has been fundamentally flawed and this has contributed to miscarriages of justice. This talk will present examples from a range of criminal cases and will highlight the special problem of mixed DNA profiles.

Biography: Norman is Professor in Risk Information Management at Queen Mary University of London, a Director of Agena, a company specialising in risk management for critical systems, and a Fellow of the Alan Turing Institute. Norman's experience in quantitative risk assessment covers a wide range of application domains, but much of his recent research has been on legal and forensic applications, notably with respect to improved analysis and presentation of probabilistic aspects of evidence using Bayesian reasoning. He has worked as an expert witness or advisor on several major criminal and civil cases. Since June 2011 he has led an international consortium (Bayes and the Law) of statisticians, lawyers and forensic scientists working to improve the use of statistics in court. In 2016 he led a 6-month Programme on Probability and Statistics in Forensic Science at the Isaac Newton Institute for Mathematical Sciences, University of Cambridge.

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Date and Time

Location

Queen Mary University of London

Mile End Road

London

E1 4NS

United Kingdom

View Map

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