Oxford crest







Dr Patrick E McSharry

Head of Forecasting and Risk Analysis
Forecasting and Risk Analysis
mcsharry AT maths.ox.ac.uk
Patrick's picture

Primary Address

Smith School of Enterprise and the Environment
University of Oxford, South Parks Road, Oxford, OX1 3QY, UK.

Secondary Address

Mathematical Institute
University of Oxford, 24-29 St Giles, Oxford, OX1 3LB, UK.

Tel: +44 1865 596778

Patrick McSharry is a Senior Research Fellow at the Smith School of Enterprise and the Environment, Faculty Member of the Oxford Man Institute of Quantitative Finance at Oxford University, Visiting Professor at the Department of Electrical and Computer Engineering, Carnegie Mellon University, Fellow of the Royal Statistical Society and Senior Member of the IEEE. He takes a multidisciplinary approach to developing quantitative techniques for data science, decision-making and risk management. His research focuses on big data, forecasting, predictive analytics, machine learning and the analysis of human behaviour. He has published over 90 peer-reviewed papers, participated in knowledge exchange programs and consults for national and international government agencies and the insurance, finance, energy, telecoms, environment and healthcare sectors. Patrick received a first class honours BA in Theoretical Physics and an MSc in Engineering from Trinity College Dublin and a DPhil in Mathematics from Oxford University.


Big Data Revolution

There is a rapid increase in the utilisation of sophisticated quantitative modelling and data analytics across the public and private sectors. With growing interest in using data to support critical decision-making and a realisation of the rewards in terms of increased efficiency and reduced risk in doing so, I have co-authored a book entitled Big Data Revolution with Rob Thomas a vice president of IBM. Our aim is to inspire business and government leaders to start using big data analytics for decision-making. We discuss the challenges and opportunities and have a number of case studies that help to provide support for the potential of using big data. Information about the book is also available as a blog.

| Home | Publications | Lectures | SSEE | | OMI | | OCIAM |