Project PI: Professor Eric T. Meyer
Eric Meyer is a Professor of Social Informatics and Director of Graduate Studies at the Oxford Internet Institute, where he has been on the faculty since 2007. Professor Meyer’s research focuses on the transition from analogue to digital technologies in research and knowledge creation across disciplines in the sciences, social sciences, arts, and humanities. His research has included both qualitative and quantitative work with marine biologists, genetics researchers, physicists, digital humanities scholars, social scientists using big data, theatre artists, librarians, and organizations involved in computational approaches to research.
Co-Investigator: Associate Professor Michael A. Osborne
Michael Osborne is a Dyson Associate Professor of Machine Learning, Official Fellow of Exeter College and Faculty Member of the Oxford-Man Institute of Quantitative Finance, all at the University of Oxford. Michael co-leads the Machine Learning Research Group, a sub-group of the Robotics Research Group in the Department of Engineering Science. Michael’s goal is to develop machine intelligence in sympathy with societal needs. Within machine learning, Michael has particular expertise in Gaussian processes, active learning, Bayesian optimisation and Bayesian quadrature, and is a founder of the emerging field of probabilistic numerics. Michael’s work in non-parametric data analytics has been successfully applied in diverse and challenging contexts. These contexts range from astrostatistics, where probabilistic algorithms have aided the detection of planets in distant solar systems, to zoology to clarify how pigeons are able to navigate such extraordinary distances.
Co-Investigator: Dr Angela Coulter
Angela Coulter is part-time senior research scientist in the Health Services Research Unit (HSRU) where her main research interest is in measuring the quality and outcomes of healthcare from the patient’s perspective. She first joined Oxford University in 1983 and was director of the HSRU from its establishment in 1991 until 1993 when she left to work for the King’s Fund in London. From 2000 to 2008 she was chief executive of Picker Institute Europe, an Oxford-based charity dedicated to researching and improving patients’ experience.
Co-Investigator: Dr Carl Benedikt Frey
Carl Benedikt is Co-Director of the Oxford Martin Programme on Technology and Employment at the Oxford Martin School, and Economics Associate of Nuffield College, both University of Oxford. He is also a Senior Fellow of the Programme on Employment, Equity and Growth at the Institute for New Economic Thinking in Oxford, and the Department of Economic History at Lund University. His research focuses the transition of industrial nations to digital economies, and subsequent challenges for economic growth, labour markets and urban development.
Reseacher: Dr Matt Willis
Matt Willis is a researcher at the Oxford Internet Institute. His research interests include sociotechnical systems in healthcare settings, patient oriented infrastructures, and health information management. His current research focuses on patient assemblages: the patterns, processes, and practices of patients use of personal health records in supporting their health and well-being. He has research experience in academic, government, and private institutional settings including Sandia National Laboratories, the U.S. Department of Veterans Affairs, and several university affiliated research centres where he was a contributor to multiple grants from the National Science Foundation (NSF), National Institutes of Health (NIH), Defence Advanced Research Projects Agency (DARPA), and Intelligence Advanced Research Projects Activity (IARPA).
Researcher: Paul Duckworth
Paul Duckworth is a Principle Researcher in the Machine Learning Research Group at University of Oxford with Mike Osborne.
He recently submitted his PhD thesis in the area of Unsupervised Human Activity Analysis for Intelligent Mobile Robots at the University of Leeds, UK.
This work focused on representing a mobile robot’s observed environment using an abstract qualitative representation, then, performing unsupervised machine learning techniques in order to recover patterns relating to observed human behaviours. It combined research across areas such as information retrieval, computer vision, robotics and Qualitative Spatial Representations.
He also has professional experience working in retail banking and performing clinical trail analysis for pharma companies.