Professor Gavin Shaddick

Gavin Shaddick

Position

Executive Dean of Engineering, Physical and Mathematical Sciences at Royal Holloway University of London

Former position

Turing Fellow, Chair of Data Science and Statistics, University of Exeter

Bio

Professor Shaddick is Executive Dean of Engineering, Physical and Mathematical Sciences at Royal Holloway University of London and co-Director of the Joint Centre for Excellence in Environmental Intelligence, a joint research centre with the UK Met Office. He is Director of the UKRI funded Centre for Doctoral Training in Environmental Intelligence: Data Science and AI for Sustainable Futures and is co-lead of the recently established theme in Environment Sustainability at The Alan Turing Institute, where he is a Turing Fellow.  He is the author of over 180 publications and co-author of two books. He is a member of the UK government’s Committee on the Medical Effects of Air Pollutants (COMEAP) and the sub-group on Quantification of Air Pollution Risk (QUARK). He leads the World Health Organization’s Data Integration Taskforce for Global Air Quality and led the development of the Data Integration Model for Air Quality (DIMAQ) that is used to calculate of a number of air pollution related United Nations Sustainable Development Goals indicators.

Research interests

Professor Shaddick's research interests include the theory and application of Bayesian hierarchical models and spatio-temporal modelling in a number of fields including epidemiology, environmental modelling, and disease progression in rheumatology. A major focus is modelling global air quality by integrating information from multiple sources, including ground monitoring, remote sensing satellites and chemical transport models.

He is also actively engaged in research with the power industry, using big data to model demand profiles, forecasting demands and identifying customer profiles. Of particular interest are computational techniques that allow the implementation of complex statistical models to real-life applications where the scope over both space and time may be very large.