Dr Anthony Webster
New approaches to the study of diseases and the relationships between them are being offered by the combination of big data and emerging machine-learning methodologies. Anthony has a 3-year NDPH fellowship to explore links between existing classifications of disease and epidemiological data. He will use a combination of established and newly emerging statistical methods to characterise the temporal and etiological characteristics of disease, and to study the relationships between them. The aims are threefold: (i) to provide new insights into the causes and consequences of disease, (ii) to develop new methods for their study and characterisation, and (iii) to understand and improve, present and future systems of disease classification.
Anthony joined NDPH in 2016 after an M.Sc. in Applied Statistics at the University of Oxford, changing career from Physics to Statistics. In addition to his statistical/epidemiological research, he is a tutor for Oxford’s Part B Statistical Lifetime Models course. Anthony's previous research includes theoretical and statistical studies of plasma stability, and a Ph.D. with Prof. Mike Cates that studied the ageing and stability of emulsions and foams.
Characterisation, identification, clustering, and classification of disease.
Webster AJ. et al, (2021), Sci Rep, 11
Multi-stage models for the failure of complex systems, cascading disasters, and the onset of disease
WEBSTER A., (2019), PLoS ONE
Insurance companies should collect a carbon levy.
Webster AJ. and Clarke RH., (2017), Nature, 549, 152 - 154
Characterisation of the deuterium recycling at the W divertor target plates in JET during steady-state plasma conditions and ELMs
Brezinsek S. et al, (2016), PHYSICA SCRIPTA, T167
Progress at JET in integrating ITER-relevant core and edge plasmas within the constraints of an ITER-like wall
Giroud C. et al, (2015), Plasma Physics and Controlled Fusion, 57