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 Safia Ahmed | ![]() |
Teaching Fellow |
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 |
Dr Horatio Boedihardjo | ![]() |
Rough path theory |
Dr Thomas Berrett | ![]() |
Developing statistical theory and methodology in nonparametric settings |
Dr Julia Brettschneider | ![]() |
Statistical methodology for high-dimensional molecular data, methodology for statistical analysis of high-throughput genomic and proteomic data. |
Dr Teresa Brunsdon | ![]() |
Associate Professor (Teaching) |
Dr Ilaria Bussoli | ![]() |
Teaching Fellow |
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Probability, statistical mechanics, stochastic analysis (especially singular Stochastic PDEs) | |
Dr Marta Catalano | ![]() |
Bayesian nonparametrics, statistical optimal transport and Wasserstein distances, stochastic processes and random measures |
Dr Avery Ching | ![]() |
Differential/difference Equations via methods in algebraic geometry and D-modules |
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Applied probability, in particular with a focus on applications in statistical physics, such as understanding the dynamics of glassy/amorphous systems and mass condensation |
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Working at the intersection of Computer Science and Statistics with research interests in machine learning and Bayesian statistics |
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Professor Xavier Didelot | ![]() |
Analysis of epidemiological and genomic data in order to understand how bacterial pathogens evolve, spread and cause diseases |
Dr Ritabrata Dutta | ![]() |
Likelihood-free Inference, Approximate Bayesian Computations, Mechanistic Network Models, Big-data Analysis, Bayes Model Selection, Bayesian Classification, Unpaired Data-Integration for Genomics and Statistical Applications in Geology, Bioinformatics and Engineering |
Dr Richard Everitt |
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Methodology for Bayesian computation, applied to statistical genetics, neuroscience, ecology, weather and climate, spatial statistics, network analysis and signal processing |
Bowen Fang | ![]() |
Teaching Fellow |
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. |
Samuel Forbes | ![]() |
Modelling and analysing the wealth distribution |
Professor Jon Forster | ![]() |
Methodological and computational statistics. Inference and prediction under model uncertainty. Statistical inference for categorical data. Demographic estimation and forecasting. |
Dr Lyudmila Grigoryeva | ![]() |
Statistical learning and analysis of dynamic processes, machine learning, reservoir computing, econometrics, time series analysis 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 |
Tim Hargreaves | ![]() |
Computational statistics, with a particular interest in Bayesian computation, Monte Carlo methods, big data methods, and deep learning |
Professor Vicky Henderson |
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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, meta-analysis and missing data. Major collaborations in cerebral palsy and epilepsy |
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AS&RU Monte Carlo methods, spatial point processes, multi-target tracking and uncertainty representation |
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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. |
Dr Jo Kennedy | ![]() |
Financial mathematics. Probability theory. Duality and time-change problems. |
Dr Alisa Kirichenko | ![]() |
Asymptotic properties of Bayesian procedures; relational data, such as networks and graphs; and performance guarantees for machine learning algorithms. High-dimensional and nonparametric methods |
Dr Jere Koskela | ![]() |
Monte Carlo methods, inference from diffusions and other stochastic processes, coalescent processes, mathematical population genetics |
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 |
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Senior Teaching Fellow | |
Professor Chenlei Leng | ![]() |
Statistical analysis of big and small datasets |
Dr Gechun Liang | ![]() |
Mathematical finance and stochastic analysis |
Professor Shahar Mendelson | ![]() |
Statistical learning theory, empirical processes theory and asymptotic geometric analysis |
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Probability, mathematical finance, statistics and numerical stochastics | |
Professor Giovanni Montana | ![]() |
Data science, especially machine learning for medical imaging and reinforcement learning |
Dr Joan Nakato |
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Senior Teaching Fellow |
Dr Sam Olesker-Taylor |
Quantifying how long it takes a randomly-evolving system to 'mix'. The canonical example is, "How many shuffles are needed to mix a deck of cards?" |
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Dr Anastasia Papavasiliou | ![]() |
Applied probability. Stochastic filtering and control. Theory of rough paths. Applications to signal processing. Multiscale systems. |
Dr Martyn Parker |
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Learner analytics, transitions to higher education, digital education |
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 |
Dr Tommaso Rosati | Singular stochastic partial differential equations, stochastic particle systems and their ergodic properties | |
Dr Asma Saleh | ![]() |
Teaching Fellow |
Professor Jim Smith |
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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 non-parametric statistics. Combinatorial stochastic processes. Measure-valued 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 |
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Approximate Bayesian computation method, likelihood-free methods, Statistical inference for stochastic processes, statistical inference for point processes |
Dr Nick Tawn | ![]() |
Computational statistics |
Dr Elke Thönnes | ![]() |
Computational statistics with emphasis on Markov chain Monte Carlo, in particular perfect simulation, and statistical image analysis |
Dr Samuel Touchard |
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Bayesian statistics |
Dr Heather Turner | ![]() |
Statistical modelling and statistical programming using the open source software R |
Dr Daniel Valesin | ![]() |
Interacting particle systems and percolation theory |
Dr Jon Warren | ![]() |
Brownian motion. Local times. Branching processes. Dynamical systems. |
Dr Yi Yu |
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High-dimensional 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, state-space models, (sequential) Monte Carlo methods, multi scale models |
Nazem Khan |
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Risk measures and their application to portfolio selection and behavioural aspects of Mathematical Finance |
Dr Michelle Kendall | ![]() |
Statistical genetics and pathogen dynamics |
Dr Francesca Crucinio | ![]() |
Computational statistics, particularly sequential Monte Carlo methods and interacting particle systems |
Dr Martina Favero (Visiting) |
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Mathematical population genetics, stochastic duality, epidemic models, inference from stochastic processes |
Dr Jorge Gonzalez Cazares |
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Simulation algorithms and convergence of Monte Carlo methods (particularly when connected to Markov, Lévy and exchangeable increment processes) |
Dr Linda Nichols |
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AS&RU |
Dr Juan Kuntz-Nussio | ![]() |
Probability, stochastic processes, applied probability, stochastic modelling, stochastic analysis, Markov processes, Markov chains, Bayesian inference, random sampling |
Dr Lionel Riou-Durand |
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Monte-Carlo methods and their theoretical guaranties, from both asymptotic and non-asymptotic point of view |
Dr Jaromir Sant | ![]() |
Probability and statistics |
Dr Aditi Shenvi |
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AS&RU Graphical models, Bayesian inference & decision making, analysis of missingness, and their applications, particularly in public health, environmental science, and social policy |
Dr Giorgos Vasdekis |
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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 |
Emeritus Professors:
Professor John Copas | Statistical modelling and inference. Models for censoring and selection bias. Local likelihood. Meta-analysis. Applications, particularly in medicine and criminology. |
Professor David Firth | Statistical theory and methods, including design and computation. Generalized linear and non-linear models. Applications, especially in the social and health sciences |
Professor Wilfrid Kendall | Stochastic differential equations. Computer algebra in probability and statistics. Applied probability especially in relation to spatial statistics. |
Professor Vassili Kolokoltsov |
Probability and stochastic processes, mathematical physics, differential equations and analysis; optimization and games with applications to business, biology and finance. |
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 |
Dr Shahin Tavakoli |
Functional data analysis, and applications to (neuro-)imaging, genomics, phonetics, biophysics, and econometrics |
Honorary Teaching Fellows:
Dr Panayiota Constantinou | Teaching Fellow |