People » Academic and research
This page lists the main research interests of Department staff. For more detailed information, follow the links to individual home pages.
Academic staff (Faculty):
Dr Larbi Alili  Probability theory and its applications. Fluctuation theory in discrete and continuous time. Exit problems for Markov processes. Fine properties of diffusions and Lévy processes.  
Dr Sigurd Assing  Probability theory, random processes, stochastic analysis, statistical mechanics and stochastic simulation.  
Dr Martine Barons (AS&RU) 
Statistical and mathematical modelling of human systems, decision support, Bayesian networks, structured expert judgement elicitation, risk and uncertainty, survival and other health outcomes 

Dr Julia Brettschneider  Statistical methodology for highdimensional molecular data, methodology for statistical analysis of highthroughput genomic and proteomic data.  
Dr Teresa Brunsdon  Associate Professor (Teaching)  
Probability, statistical mechanics, stochastic analysis (especially singular Stochastic PDEs)  
Applied probability, in particular with a focus on applications in statistical physics, such as understanding the dynamics of glassy/amorphous systems and mass condensation 

Senior Teaching Fellow  
Associate Professor (Teaching)  
Working at the intersection of Computer Science and Statistics with research interests in machine learning and Bayesian statistics 

Professor Xavier Didelot  Analysis of epidemiological and genomic data in order to understand how bacterial pathogens evolve, spread and cause diseases  
Dr Ritabrata Dutta  Likelihoodfree Inference, Approximate Bayesian Computations, Mechanistic Network Models, Bigdata Analysis, Bayes Model Selection, Bayesian Classification, Unpaired DataIntegration for Genomics and Statistical Applications in Geology, Bioinformatics and Engineering  
Dr Richard Everitt 
Methodology for Bayesian computation, applied to statistical genetics, neuroscience, ecology, weather and climate, spatial statistics, network analysis and signal processing 

Professor Bärbel Finkenstädt Rand  Time series analysis and dynamical systems. Periodic time series and oscillations in biological systems. Parameter estimation for (stochastic) differential equations. Molecular population dynamics. Genetic regulatory systems.  
Professor David Firth  Statistical theory and methods, including design and computation. Generalized linear and nonlinear models. Applications, especially in the social and health sciences.  
Professor Jon Forster 
Methodological and computational statistics. Inference and prediction under model uncertainty. Statistical inference for categorical data. Demographic estimation and forecasting. 

Professor Simon French 
Decision Analysis; Decision Support; Risk Analysis and Communication; Statistical Techniques; Information Systems; Collaboration and the Web; Public Sector; Environmental Management; Emergency Management  
Professor Vicky Henderson 
Optimal stopping and optimal control problems, with applications to real options, executive stock options, and recently, behavioural finance  
Dr Martin Herdegen  Arbitrage theory, change of numéraire, utility maximisation, financial bubbles, transaction costs, equilibria, semimartingale calculus, strict local martingales  
Professor David Hobson  Probability and financial mathematics  
Professor Jane Hutton  Medical statistics, with special interests in survival analysis, metaanalysis and missing data. Major collaborations in cerebral palsy and epilepsy  
Dr Jeremie Houssineau  Monte Carlo methods, spatial point processes, multitarget tracking and uncertainty representation  
Professor Saul Jacka  Stochastic differential equations. Stochastic control. Applied stochastic processes. Optimal stopping. Applications of probability in finance and economics  
Dr Paul Jenkins 
Monte Carlo methods, inference from stochastic processes, mathematical population genetics, data science and genomics 

Dr Adam Johansen  Monte Carlo Methods, Computational statistics. Time series. Bayesian inference and decision making.  
Professor Wilfrid Kendall  Stochastic differential equations. Computer algebra in probability and statistics. Applied probability especially in relation to spatial statistics.  
Dr Jo Kennedy  Financial mathematics. Probability theory. Duality and timechange problems.  
Dr Jere Koskela  Monte Carlo methods, inference from diffusions and other stochastic processes, coalescent processes, mathematical population genetics  
Professor Vassili Kolokoltsov  Probability and stochastic processes, mathematical physics, differential equations and analysis; optimization and games with applications to business, biology and finance.  
Dr Ioannis Kosmidis  Methods for optimal estimation and inference of statistical models, inference and computation of statistical models from big data sets, clustering methods and applications.  
Dr Krzysztof Łatuszyński  Markov chain Monte Carlo, adaptive Monte Carlo, stochastic simulations and Bayesian statistics  
Senior Teaching Fellow  
Professor Chenlei Leng  Statistical analysis of big and small datasets  
Dr Gechun Liang  Mathematical finance and stochastic analysis  
Probability, mathematical finance, statistics and numerical stochastics  
Dr Joan Nakato 
Senior Teaching Fellow  
Dr Anastasia Papavasiliou  Applied probability. Stochastic filtering and control. Theory of rough paths. Applications to signal processing. Multiscale systems.  
Dr Martyn Parker 
Associate Professor (Teaching)  
Professor Martyn Plummer  Biostatistics, cancer epidemiology, statistical computing and Markov Chain Monte Carlo  
Dr Yan Qu 
Teaching Fellow  
Professor Christian Robert  Bayesian analysis, computational statistics, latent variable models and applied modelling  
Professor Gareth Roberts  Stochastic processes, computational statistics, Bayesian statistics and mathematical finance  
Professor Jim Smith (AS&RU) 
Environmental modelling. Game theory. Bayesian decision theory. Foundations of statistics. Business time series. Influence diagrams. Graphical methods.  
Dr Dario Spanò  Mathematical population genetics. Bayesian nonparametric statistics. Combinatorial stochastic processes. Measurevalued processes.  
Dr Simon Spencer 
Bayesian inference applied to epidemiology, stochastic epidemic models and statistics for analytical science 

Professor Mark Steel  Bayesian statistics and econometrics. Modelling of skewness. Spatial statistics. Model uncertainty. Semi and nonparametric Bayes.  
Dr Massimiliano Tamborrino 
Approximate Bayesian computation method, likelihoodfree methods, Statistical inference for stochastic processes, statistical inference for point processes 

Dr Shahin Tavakoli 
Functional Data Analysis (Theory, Methods and Applications). Methodological developments driven by applications in Phonetics, Imaging, and Biophysics 

Dr Nick Tawn  Computational statistics  
Dr Elke Thönnes  Reader (Teaching)  
Dr Samuel Touchard 
Senior Teaching Fellow 

Dr Sebastian Vollmer 
Monte Carlo Methods, Stochastic Gradient Methods, Stochastic Processes 

Professor David Wild  Statistical bioinformatics; in particular in the application of Bayesian statistical machine learning techniques to problems in systems biology, functional genomics and proteomics  
Dr Wei Wu  Probability and mathematical physics (random fields, spin models, spanning trees, percolation)  
Dr Jon Warren  Brownian motion. Local times. Branching processes. Dynamical systems.  
Dr Yi Yu 
Highdimensional statistics, network studies, survival analysis and applications in brain imaging data 
Research Fellows:
Dr Anna Brestovitsky (ATI) 
Social data science and research methods  
Dr Jake Carson  Exact inference for Partial Differential Equations  
Dr Alice Corbella  Inference and prediction in epidemic models. Bayesian evidence synthesis, stochastic processes, statespace models, (sequential) Monte Carlo methods, multi scale models  
Dr Susana Conde Llinares (ATI)  Statistical modelling, high dimensional networks, sparse multidimensional contingency tables, mixed models, penalised likelihood, hierarchical loglinear models, cluster analysis, causal inference  
Dr Thais Fonseca (AS&RU) 
Bayesian inference for stochastic processes, mainly spatial and spatiotemporal models; Clustering of time series; Dynamical and multilevel models  
Dr Elena Hernandez Hernandez 
Stochastic control in continuous time, and fractional differential equations and their connection with probability theory 

Dr Qi Huang  Sstatistical modelling of chronobiology and circadian rhythm data  
Dr Kathryn Leeming 
Methodology for data problems in time series analysis  
Dr Sherman Lo 
Applied statistics, Computational statistics, Machine leaning and image analysis 

Dr Linda Nichols (AS&RU) 
Statistical analysis of large observational cohort studies and clinical trials and interested in the use of electronic patient records for research. 

Dr Lionel RiouDurand 
MonteCarlo methods and their theoretical guaranties, from both asymptotic and nonasymptotic point of view  
Dr Panayiota Touloupou  Bayesian inference and model selection for partially observed stochastic epidemics  
Dr Jure Vogrinc 
Markov chain Monte Carlo, optimal scaling, variance reduction. Rare event simulation 

Dr Jun Yang 
Statistical learning theory, computational statistics, Bayesian inference, highdimensional statistics, and applied probability 
Emeritus Professors:
Professor John Copas  Statistical modelling and inference. Models for censoring and selection bias. Local likelihood. Metaanalysis. Applications, particularly in medicine and criminology. 
Professor Tony Lawrance  Statistical analysis and nonlinear modelling of financial time series. 
Honorary Professors:
Dr Tim Davis  Statistical applications in engineering 
Professor Valerie Isham  
Professor Thomas Nichols  
Dr David Rossell 
Associate Fellows:
Dr David Croydon  Probability theory 
Dr Rachel Hilliam 
Honorary Research Fellows:
Dr John Fenlon  
Dr Heather Turner  Statistical modelling and statistical programming using the open source software R 