stat sci heading
A regression-based post-processing of the climate model output leads to improved forecasts almost everywhere. (Siegert et al, 2016)
Sequentially ruling out unrealistic parameter values leads to computer model output that is closer to the real world. (Salter et al, 2018)
A statistical emulator predicts the mean and uncertainty of the chaotic Lorenz attractor. (Mohammadi et al, 2018)
Global map of particulate matter (PM2.5) concentration at 0.1 x 0.1 degree resolution. (Shaddick et al, 2018)
Expected annual storm rates and uncertainties derived from a generalised additive point process model. (Youngman et al, 2018)
Our research aims to improve understanding, prediction and management of complex systems by developing and applying statistical methods for analyzing and interpreting computer simulations and integrating them with physical measurements and expert judgment.
Research
We work on a wide range of exciting research topics, including environmental hazards, air quality modeling, calibration of computer models, forecast verification and spatial epidemiology.
To find out more visit our research themes page.
Postgraduate research
We welcome enquiries from prospective PhD students. View our selection of PhD research topics, you can also find more under the personal web pages of the group members.
