Dear visitor no. 44320 *

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Bio:

My research interests lie in Bayesian Artificial Intelligence. I specialise in Bayesian Network (BN) theory and modelling for prediction, uncertainty quantification, risk and decision analysis in real-world situations. I apply my research to a wide range of fields, for both academic research and industrial organisations, including sports, forensics, project management, medicine, agriculture, software reliability, gambling and gaming. Most of my research is driven by acknowledging the limitations of classical statistics and automated learning algorithms for optimal real-world decision making, and inventing methods that incorporate ‘causal intelligence’ to the process of data engineering, and real-world ‘causal facts’ to the process of Bayesian modelling, driven by what information we really require for inference rather than blindly seeking ‘bigger’ data.

Currently, I am Post-Doctoral Researcher at the Risk & Information Management (RIM) Research Group, School of Electronic Engineering and Computer Science, Queen Mary, University of London. I work on the project 'Effective Bayesian Modelling with Knowledge before Data' which is funded by the European Research Council (ERC) and involves the improvement of evidence-based decision making for real-world critical decision problems.

I also work as a freelance Decision Science consultant for clients world-wide primarily in, but not limited to, the sports betting industry. I am also the founder of www.pi-football.com ; a website that provides free English Premier League football match predictions, since league season beginning August 2010, based on algorithms and models developed during my Ph.D.

Previously I was Post-Doctoral Research Fellow at Barts and The London School of Medicine, Queen Mary, University of London. I worked on the project 'Improving Risk Management in Mental Health Services', funded by the NIHR. The project involved the development of BN models for risk and decision analysis in forensic psychiatry.