Statistics & Probability PhD Research. 15th November 2014

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1 Statistics & Probability PhD Research 15th November

2 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.

3 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

4 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

5 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)

6 More Information & Contacts Department Research webpages Graduate school webpages Admissions contacts: Karsten Matthies (Pure & Applied Mathematics) Simon Harris (Probability and Statistics) SAMBA (Centre for Doctoral Training) Faculty of Science Graduate school

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