Statistics & Probability PhD Research 15th November 2014 1
Statistics Statistical research is the development and application of methods to infer underlying structure from data. Broad areas of statistics research at Bath: Environmental and epidemiological statistics air pollution & effects on health; forest health & climate change; animal abundance; ecology; energy forecasting; etc. Medical statistics design & analysis of clinical trials Statistical computing MCMC simulation methods; reliable & efficient computational methods for semiparametric and mixed models; etc. Smoothing and functional data penalised regression spline smoothing; modelling human movement; etc. Bayesian statistics using prior information in models for complex problems with many sources of randomness: partial prior specification; optimal criteria for prior selection; image analysis; software testing; etc.
Statisticians Karim Anaya-Izquierdo - Statistical Inference, Differential Geometry, Survival Analysis, Statistical Computation, Spatial Epidemiology Nicole Augustin - spatial and spatio-temporal statistics applied in the environmental sciences or in epidemiology (eg. modelling physical activity in relation to other health outcomes such as obesity) Evangelos Evangelou - spatial statistics, time series Julian Faraway - Functional data analysis, shape statistics, applied statistics Merrilee Hurn - Markov chain Monte Carlo methods, particularly with applications in image analysis, Bayesian mixture modelling, and Bayesian methodology Chris Jennison - Statistical methods for the design and analysis of clinical trials Finn Lindgren - Stochastic modelling and random fields, Spatial and space-time statistics, Climate and animal abundance data, Computational statistics Tony Robinson - Bayesian statistics applied in education & biology Gavin Shaddick - spatial statistics, epidemiology, environmental modelling particularly air pollution Simon Shaw - Bayesian approaches to statistics, Bayes linear methods, exchangeable sequences, graphical models Simon Wood - generalised additive modelling applied in energy forecasting and ecology
Probability Probability theory is mainly concerned with the development, analysis, and application of mathematical models describing randomness or noise'. Broad areas of probability research at Bath: Brownian motion mathematical model for Brown s pollen grains jiggling in water; scaling limit of random walk. Random graphs & Random networks eg. the world-wide web Self-organised criticality eg. avalanche (sandpile) models Percolation & Interacting particle systems eg. spread of forest fires, or water percolating through rocks; models of voting behaviour; etc. Lévy processes & self-similar Markov processes processes with special properties that allow jumps Branching, fragmentation & coalescent processes eg. spread of disease, genealogies of populations, computer algorithms etc. Mathematical finance eg. how to price assets and hedge against risk Related areas include: Analysis and Differential Equations, Mathematical biology, Numerical Analysis, Statistics
Probabilists Alex Cox - mathematical finance, option pricing, optimal martingale transport, Skorokod embedding, robustness, optimal control/stopping Simon Harris - branching processes, branching Brownian motion, martingale & spine methods, FKPP & reaction-diffusion equations, coalescence, fragmentation. Antal Jarai - self-organising processes, random walks on fractals, sandpile models Andreas Kyprianou - Levy processes, positive self-similar Markov processes, fragmentation, coalescence, branching processes, numerical SDE, optimal stopping, math finance/insurance Peter Moerters - random networks, condensation processes. Mathew Penrose - stochastic geometry; continuous percolation, interacting particle systems with spatial deposition, random packing, spatial random networks Matt Roberts - branching Brownian motion, branching random walks, fragmentation & coalescent processes, random graphs. Alexandre Stauffer - random interacting systems; random walks in dynamic environments, random graphs, self-organising processes, sandpile models. Related supervisors: Tim Rogers (random networks & models with spatial structure), Tony Shardlow (SDEs & numerical analysis)
More Information & Contacts Department Research webpages www.bath.ac.uk/math-sci/postgraduate/ Graduate school webpages www.bath.ac.uk/science/gradschool/ Admissions contacts: Karsten Matthies (Pure & Applied Mathematics) k.matthies@bath.ac.uk Simon Harris (Probability and Statistics) s.c.harris@bath.ac.uk SAMBA (Centre for Doctoral Training) samba@bath.ac.uk Faculty of Science Graduate school fsci-pgadmissions@bath.ac.uk