����Vlog

Applied statistics has a rich history at ����Vlog. Researchers in this group have developed influential statistical methods that have shaped research and practice across many fields.

Notable achievements include Emeritus Professor Robert Curnow’s pioneering work on optimal selection strategies in animal and plant breeding, and the Nelder-Mead algorithm (or simplex method), co-developed by Professor Roger Mead. This widely used algorithm remains one of the most influential methods in numerical optimisation, with more than 20,000 citations and applications in software used worldwide.

Our current research continues in this tradition. We develop new statistical methods to analyse large and complex data sets, helping to address challenges across a range of disciplines in the era of “big data”.

Statistics for biology and health

• Professor Sue Todd specialises in medical statistics, with a particular focus on adaptive designs. Her research combines the development of new methods for study design and analysis with applied work that supports the use of these statistical methods in healthcare. She has expertise in adaptive and platform clinical trials, and collaborates with both the pharmaceutical industry and public sector institutions.
• Dr Fazil Baksh conducts research into statistical genetics, focussing on genome-wide association studies, family genetics and population genetics using whole-genome data.
• Professor Marcus Tindall is interested in mathematical biology, which aligns closely with this theme.

Data science

• Dr Fazil Baksh focuses on the foundational statistical principles that drive machine learning. His research explores why machine learning techniques work, drawing on statistical inference and modelling to interrogate concepts such as robustness, interpretability and generalisability.
• Dr Jochen Broecker is interested in applications of machine learning to weather, climate and oceans.
• Dr Eviatar Bach studies machine learning for inverse problems and data assimilation, in particular looking to integrate machine learning and data assimilation for forecasting and predictability.
• Dr Zuowei Wang combines machine learning, statistical sampling methods, mathematical modelling and computer simulations to address research challenges across a range of disciplines. His work spans antimicrobial peptides, biological and synthesised macromolecules, complex fluids, food science and rare climate events.
• Dr Jeroen Wouters specialises in environmental modelling, using machine learning techniques together with computer simulations to predict rare events.