Hosted by the Brunel Centre for Mathematical and Statistical Modelling
Statistical and mathematical modelling underpins much of the research that is done at Brunel (and of course worldwide), and mathematics and statistics tends to be seen as a tool that is used implicitly by researchers in many disciplines to get answers. For example:
• Engineers will use a computer model to simulate catastrophic failure within an aircraft wing,
• Health scientists will use population models to simulate the spread of COVID-19 under various lockdown scenarios
• Economists plot paths for financial systems under various fiscal interventions.
It turns out in many cases that small changes in model assumptions lead to very large changes in conclusions, and a major theme of the research within the newly-formed Brunel Centre for Mathematical and Statistical Modelling is assessing the quality of these models and how the scientific conclusions vary under different model assumptions, and data collection regimes.
Prof. Rosemary Bailey (St Andrew's University)
Dr Olga Egorova ( King's College London)
Prof. Steven Gilmour (King's College London)
Dr Hugo Maruri-Aguilar (Queen Mary, University of London)
Dr Robin Mitra (UCL)
Dr Antony Overstall (Southampton University)
Dr Dasha Semochkina (University of Southampton)
Dr Tim Waite (Manchester University)
Please contact ben.parker@brunel.ac.uk with any queries.