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):
Professor Keith Abrams 
Bayesian statistical methods, design & Analysis of RCTs, Evidence Synthesis and Health Data Science 

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 Horatio Boedihardjo  Rough path theory  
Dr Thomas Berrett 
Developing statistical theory and methodology in nonparametric settings 

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 

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 FinkenstädtRand  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 Jon Forster 
Methodological and computational statistics. Inference and prediction under model uncertainty. Statistical inference for categorical data. Demographic estimation and forecasting. 

Dr Karen Habermann  Stochastic analysis with connections to geometry, analysis, and numerics, and with a particular interest in hypoelliptic diffusion processes on manifolds  
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 

Professor 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 Alisa Kirichenko  Asymptotic properties of Bayesian procedures; relational data, such as networks and graphs; and performance guarantees for machine learning algorithms. Highdimensional and nonparametric methods  
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.  
Professor 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  
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  
Dr Leonardo Rolla  Random Spatial Processes, Percolation, and Particle Systems  
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 Nick Tawn  Computational statistics  
Dr Elke Thönnes  Reader (Teaching)  
Dr Samuel Touchard 
Senior Teaching Fellow 

Dr Heather Turner 
Statistical modelling and statistical programming using the open source software R 

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

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 Alice Corbella  Inference and prediction in epidemic models. Bayesian evidence synthesis, stochastic processes, statespace models, (sequential) Monte Carlo methods, multi scale models  
Dr Michelle Kendall  Statistical genetics and pathogen dynamics  
Francesca Crucinio  Computational statistics, particularly sequential Monte Carlo methods and interacting particle systems  
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 Juan KuntzNussio  Probability, stochastic processes, applied probability, stochastic modelling, stochastic analysis, Markov processes, Markov chains, Bayesian inference, random sampling  
Dr Ares Panos  Machine learning  
Dr Lionel RiouDurand 
MonteCarlo methods and their theoretical guaranties, from both asymptotic and nonasymptotic point of view  
Dr Giorgos Vasdekis 
Markov Chain Monte Carlo techniques and their applications in Bayesian Statistics  
Dr Jure Vogrinc 
Markov chain Monte Carlo, optimal scaling, variance reduction. Rare event simulation 

Dr Haotian Xu 
Time series, robust statistics, high dimensional statistics, heavy tails, limit theory, empirical processes, signal processing and change point detection 
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 David Firth  Statistical theory and methods, including design and computation. Generalized linear and nonlinear models. Applications, especially in the social and health sciences 
Professor Tony Lawrance  Statistical analysis and nonlinear modelling of financial time series. 
Professor David Wild  Statistical bioinformatics 
Honorary Professors:
Dr Tim Davis  Statistical applications in engineering 
Professor Valerie Isham  Applied Probability 
Associate Fellows:
Dr Rachel Hilliam 
Pedgogical projects in mathematics and statistics 
Dr Murray Pollock 
Computational statistics, Cryptography, Monte Carlo methodology, Perfect simulation, Risk modelling, Stochastic differential equations 
Honorary Teaching Fellows:
Dr Panayiota Constantinou  Teaching Fellow 