Bayesian Argumentation via Delphi

Bayesian Reasoning For Better Thinking

Prof Martin Neil

Martin Neil is a Professor in Computer Science and Statistics in Queen Mary, University of London and is also a joint founder of Agena. His research interests cover Bayesian modeling and risk quantification in diverse areas. His experience in applying Bayesian methods to real problems has convinced him that intelligent risk assessment and decision analysis requires knowledge and data, not just “Big Data”.

He is interested in intelligent risk assessment and decision analysis using knowledge and data. Typically, this involves analysing and predicting the probabilities of unknown events using Bayesian statistical methods including causal, probabilistic models (Bayesian networks).

In addition to working on theoretical and algorithmic foundations, this work covers a wide range of application domains such as medical analytics, legal reasoning, embedded software, operational risk in finance, systems and design reliability (including software), project risk,commercial risk, decision support, cost benefit analysis, AI and personalization, machine learning, legal argumentation, cyber security and football prediction.

    The BARD project is funded by IARPA’s CREATE Program