Management Team
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The following faculty form the Supervisory Pool for OxWaSP:
Dr Cedric Archambeau (Amazon, Berlin, Germany)
Probabilistic machine learning, approximate inference, Bayesian optimization; representation learning, transfer learning, continual learning, and resource-efficient learning.
cedrica@amazon.com
Probabilistic machine learning, approximate inference, Bayesian optimization; representation learning, transfer learning, continual learning, and resource-efficient learning.
cedrica@amazon.com
Professor Julien Berestycki (Oxford)
Branching processes, branching random walks, coalescence, fragmentation, population genetics, reaction-diffusion equations, front propagation, random trees.
berestyc@stats.ox.ac.uk
Branching processes, branching random walks, coalescence, fragmentation, population genetics, reaction-diffusion equations, front propagation, random trees.
berestyc@stats.ox.ac.uk
Dr Julia Brettschneider (Warwick)
Statistical methodology for high-dimensional molecular data. Methodology for analysis of high-throughput genomic and proteomic data.
J.A.Brettschneider@warwick.ac.uk
Statistical methodology for high-dimensional molecular data. Methodology for analysis of high-throughput genomic and proteomic data.
J.A.Brettschneider@warwick.ac.uk
Professor Francois Caron (Oxford)
Bayesian nonparametrics, computational statistics, statistical machine learning, networks.
caron@stats.ox.ac.uk
Bayesian nonparametrics, computational statistics, statistical machine learning, networks.
caron@stats.ox.ac.uk
Dr Mingli Chen (Warwick)
My research fields are Econometrics, Time Series Econometrics, Financial Econometrics and Industrial Organization.
M.Chen.3@warwick.ac.uk
My research fields are Econometrics, Time Series Econometrics, Financial Econometrics and Industrial Organization.
M.Chen.3@warwick.ac.uk
Professor Mihai Cucuringu (Oxford)
Development and mathematical & statistical analysis of algorithms that extract information from massive noisy data. Inverse problems on large graphs with applications in machine learning and network analysis. Spectral and semidefinite programming algorithms for ranking, clustering, group synchronization, phase unwrapping. Time series analysis. Statistical analysis of financial data, statistical arbitrage, limit order books, risk models. mihai.cucuringu@stats.ox.ac.uk
Development and mathematical & statistical analysis of algorithms that extract information from massive noisy data. Inverse problems on large graphs with applications in machine learning and network analysis. Spectral and semidefinite programming algorithms for ranking, clustering, group synchronization, phase unwrapping. Time series analysis. Statistical analysis of financial data, statistical arbitrage, limit order books, risk models. mihai.cucuringu@stats.ox.ac.uk
Dr Theo Damoulas (Warwick)
My research interests are in machine learning and Bayesian statistics with a focus on spatio-temporal problems in urban science and computational sustainability.
T.Damoulas@warwick.ac.uk
My research interests are in machine learning and Bayesian statistics with a focus on spatio-temporal problems in urban science and computational sustainability.
T.Damoulas@warwick.ac.uk
Professor Charlotte Deane (Oxford)
Protein structure evolution. Protein structure prediction. Analysis of protein-protein interactions.
deane@stats.ox.ac.uk
Protein structure evolution. Protein structure prediction. Analysis of protein-protein interactions.
deane@stats.ox.ac.uk
Professor George Deligiannidis (Oxford)
Computational statistics, analysis of Monte Carlo methods, limit theorems for stochastic processes, random walks in lattices.
deligian@stats.ox.ac.uk
Computational statistics, analysis of Monte Carlo methods, limit theorems for stochastic processes, random walks in lattices.
deligian@stats.ox.ac.uk
Professor Xavier Didelot (Warwick)
Statistical genetics, infectious disease epidemiology, Bayesian inference, Monte Carlo methods.
Xavier.Didelot@warwick.ac.uk
Statistical genetics, infectious disease epidemiology, Bayesian inference, Monte Carlo methods.
Xavier.Didelot@warwick.ac.uk
Professor Arnaud Doucet (Oxford)
Bayesian statistics; Stochastic Simulation; Sequential Monte Carlo; Markov Chain Monte Carlo; Time Series.
doucet@stats.ox.ac.uk
Bayesian statistics; Stochastic Simulation; Sequential Monte Carlo; Markov Chain Monte Carlo; Time Series.
doucet@stats.ox.ac.uk
Dr Rito Dutta (Warwick)
Likelihood-free Inference, Approximate Bayesian Computations, Mechanistic Network Models, Model Selection, Applications of Statistics in Natural Science (e.g. Epidemiology, Bio-simulation etc.).
Ritabrata.Dutta@warwick.ac.uk
Likelihood-free Inference, Approximate Bayesian Computations, Mechanistic Network Models, Model Selection, Applications of Statistics in Natural Science (e.g. Epidemiology, Bio-simulation etc.).
Ritabrata.Dutta@warwick.ac.uk
Professor Alison Etheridge (Oxford)
Infinite dimensional stochastic processes and their applications. Mathematical problems in population genetics.
etheridge@stats.ox.ac.uk
Infinite dimensional stochastic processes and their applications. Mathematical problems in population genetics.
etheridge@stats.ox.ac.uk
Professor Robin Evans (Oxford)
My research is geared towards detecting and quantifying causal mechanisms from non-experimental data, and understanding when this is impossible. To that end, I work mainly on graphical models, algebraic statistics and model selection problems.
evans@stats.ox.ac.uk
My research is geared towards detecting and quantifying causal mechanisms from non-experimental data, and understanding when this is impossible. To that end, I work mainly on graphical models, algebraic statistics and model selection problems.
evans@stats.ox.ac.uk
Professor Bärbel Finkenstädt Rand (Warwick)
Time series analysis and dynamical systems. Periodic time series and oscillations in biological systems. Parameter estimation for (stochastic) differential equations.
B.F.Finkenstadt@warwick.ac.uk
Time series analysis and dynamical systems. Periodic time series and oscillations in biological systems. Parameter estimation for (stochastic) differential equations.
B.F.Finkenstadt@warwick.ac.uk
Professor David Firth (Warwick)
Statistical theory and methods, including design and computation. Generalized linear and non-linear models. Applications, especially in the social and health sciences.
D.Firth@warwick.ac.uk
Statistical theory and methods, including design and computation. Generalized linear and non-linear models. Applications, especially in the social and health sciences.
D.Firth@warwick.ac.uk
Professor Yarin Gal (Oxford)
Machine learning, Bayesian deep learning, approximate Bayesian inference, Gaussian processes, Bayesian non-parametrics, generative modelling, AI safety, ML interpretability, reinforcement learning, active learning, natural language processing, computer vision, medical analysis.
yarin@cs.ox.ac.uk
Machine learning, Bayesian deep learning, approximate Bayesian inference, Gaussian processes, Bayesian non-parametrics, generative modelling, AI safety, ML interpretability, reinforcement learning, active learning, natural language processing, computer vision, medical analysis.
yarin@cs.ox.ac.uk
Professor Jotun Hein (Oxford)
Sequence Analysis, Genome Annotation and Statistical Alignment. Phylogenies, Pedigrees and Recombination. Integrative Genomics and Data Fusion. Comparative Biology
hein@stats.ox.ac.uk
Sequence Analysis, Genome Annotation and Statistical Alignment. Phylogenies, Pedigrees and Recombination. Integrative Genomics and Data Fusion. Comparative Biology
hein@stats.ox.ac.uk
Dr Vicky Henderson (Warwick)
Optimal stopping and optimal control problems, with applications to real options, executive stock options, and recently, behavioural finance
Vicky.Henderson@warwick.ac.uk
Optimal stopping and optimal control problems, with applications to real options, executive stock options, and recently, behavioural finance
Vicky.Henderson@warwick.ac.uk
Dr Martin Herdegen (Warwick)
Arbitrage theory, change of numéraire, utility maximisation, financial bubbles, transaction costs, equilibria (with and without frictions). Semimartingale calculus, strict local martingales, processes with jumps.
M.Herdegen@warwick.ac.uk
Arbitrage theory, change of numéraire, utility maximisation, financial bubbles, transaction costs, equilibria (with and without frictions). Semimartingale calculus, strict local martingales, processes with jumps.
M.Herdegen@warwick.ac.uk
Professor Chris Holmes (Oxford)
Bayesian Statistics. Statistical genetics and genomics. Methods and computation for big data. Nonparametric regression and machine learning methods.
cholmes@stats.ox.ac.uk
Bayesian Statistics. Statistical genetics and genomics. Methods and computation for big data. Nonparametric regression and machine learning methods.
cholmes@stats.ox.ac.uk
Professor Jane Hutton (Warwick)
Missing data, chain event graphs, life time data analysis.
J.L.Hutton@warwick.ac.uk
Missing data, chain event graphs, life time data analysis.
J.L.Hutton@warwick.ac.uk
Professor Saul Jacka (Warwick)
Stochastic differential equations. Stochastic control. Applied stochastic processes. Optimal stopping. Applications of probability in finance and economics.
S.D.Jacka@warwick.ac.uk
Stochastic differential equations. Stochastic control. Applied stochastic processes. Optimal stopping. Applications of probability in finance and economics.
S.D.Jacka@warwick.ac.uk
Dr Paul Jenkins (Warwick)
Monte Carlo methods, mathematical genetics, Bayesian nonparametrics.
P.Jenkins@warwick.ac.uk
Monte Carlo methods, mathematical genetics, Bayesian nonparametrics.
P.Jenkins@warwick.ac.uk
Dr Adam Johansen (Warwick)
Monte Carlo Methods (particularly Sequential Monte Carlo), Computational statistics, Bayesian inference (particularly for time series).
A.M.Johansen@warwick.ac.uk
Monte Carlo Methods (particularly Sequential Monte Carlo), Computational statistics, Bayesian inference (particularly for time series).
A.M.Johansen@warwick.ac.uk
Prof Varun Kanade (Oxford)
Computational and statistical learning theory; machine learning theory; online learning; randomized algorithms; theoretical computer science.
varunk@cs.ox.ac.uk
Computational and statistical learning theory; machine learning theory; online learning; randomized algorithms; theoretical computer science.
varunk@cs.ox.ac.uk
Professor Wilfrid Kendall (Warwick)
Stochastic differential equations. Computer algebra in probability and statistics. Applied probability especially in relation to spatial statistics.
W.S.Kendall@warwick.ac.uk
Stochastic differential equations. Computer algebra in probability and statistics. Applied probability especially in relation to spatial statistics.
W.S.Kendall@warwick.ac.uk
Dr Jo Kennedy (Warwick)
Financial mathematics. Probability theory. Duality and time-change problems.
J.E.Kennedy@warwick.ac.uk
Financial mathematics. Probability theory. Duality and time-change problems.
J.E.Kennedy@warwick.ac.uk
Dr Jere Koskela (Warwick)
Monte Carlo methods, inference from diffusions and other stochastic processes, coalescent processes, mathematical population genetics
j.koskela@warwick.ac.uk
Monte Carlo methods, inference from diffusions and other stochastic processes, coalescent processes, mathematical population genetics
j.koskela@warwick.ac.uk
Professor Pawan Kumar (Oxford)
Continuous and discrete optimisation for machine learning; machine learning for continuous and discrete optimisation.
pawan@robots.ox.ac.uk
Continuous and discrete optimisation for machine learning; machine learning for continuous and discrete optimisation.
pawan@robots.ox.ac.uk
Dr Krzystof Łatuszyński (Warwick)
Markov chain Monte Carlo, adaptive Monte Carlo, stochastic simulations and Bayesian statistics.
K.G.Latuszynski@warwick.ac.uk
Markov chain Monte Carlo, adaptive Monte Carlo, stochastic simulations and Bayesian statistics.
K.G.Latuszynski@warwick.ac.uk
Professor Chenlei Leng (Warwick)
Large-scale interference, interface between computational scalability and statistical optimality, statistics of networks.
C.Leng@warwick.ac.uk
Large-scale interference, interface between computational scalability and statistical optimality, statistics of networks.
C.Leng@warwick.ac.uk
Professor James Martin (Oxford)
Probability, interacting particle systems, models of random growth and percolation, processes of coagulation and fragmentation, random graphs.
martin@stats.ox.ac.uk
Probability, interacting particle systems, models of random growth and percolation, processes of coagulation and fragmentation, random graphs.
martin@stats.ox.ac.uk
Dr Patrick McSharry (Oxford)
Time series modelling, machine learning, signal processing, and systems analysis.
patrick@mcsharry.net
Time series modelling, machine learning, signal processing, and systems analysis.
patrick@mcsharry.net
Professor Alex Mijatovic (Warwick)
Numerical stochastics, mathematical finance, statistics, probability.
a.mijatovic@warwick.ac.uk
Numerical stochastics, mathematical finance, statistics, probability.
a.mijatovic@warwick.ac.uk
Professor Simon Myers (Oxford)
Population genetics. Methods to map disease genes in admixed populations, and methods for fine-mapping association signals.
myers@stats.ox.ac.uk
Population genetics. Methods to map disease genes in admixed populations, and methods for fine-mapping association signals.
myers@stats.ox.ac.uk
Professor Geoff Nicholls (Oxford)
Bayesian inference, Statistical Methods, Computational Statistics, Monte Carlo, Statistical Genetics, Applied Statistics.
nicholls@stats.ox.ac.uk
Bayesian inference, Statistical Methods, Computational Statistics, Monte Carlo, Statistical Genetics, Applied Statistics.
nicholls@stats.ox.ac.uk
Professor Thomas Nichols (Oxford)
Statistical methods for the analysis of brain image data.
thomas.nichols@bdi.ox.ac.uk
Statistical methods for the analysis of brain image data.
thomas.nichols@bdi.ox.ac.uk
Dr Mike Osborne (Oxford)
Probabilistic numerics. Bayesian inference. Gaussian processes.
mosb@robots.ox.ac.uk
Probabilistic numerics. Bayesian inference. Gaussian processes.
mosb@robots.ox.ac.uk
Professor Pier Francesco Palamara (Oxford)
Computational methods for population genetics (natural selection, demographic history); statistical genetics (complex trait heritability, association); scalable methods for large genomic data sets.
palamara@stats.ox.ac.uk
Computational methods for population genetics (natural selection, demographic history); statistical genetics (complex trait heritability, association); scalable methods for large genomic data sets.
palamara@stats.ox.ac.uk
Dr Anastasia Papavasiliou (Warwick)
Applied probability. Stochastic filtering and control. Theory of rough paths. Applications to signal processing. Multiscale systems.
A.Papavasiliou@warwick.ac.uk
Applied probability. Stochastic filtering and control. Theory of rough paths. Applications to signal processing. Multiscale systems.
A.Papavasiliou@warwick.ac.uk
Professor Martyn Plummer (Warwick)
Biostatistics, cancer epidemiology, statistical computing (particularly R), and Markov Chain Monte Carlo methods.
Martyn.Plummer@warwick.ac.uk
Biostatistics, cancer epidemiology, statistical computing (particularly R), and Markov Chain Monte Carlo methods.
Martyn.Plummer@warwick.ac.uk
Dr Murray Pollock (Warwick)
Algorithmic design; Bayesian inference; Monte Carlo methodology; Perfect simulation; Scalable methods for big data and big models; Stochastic differential equations.
m.pollock@warwick.ac.uk
Algorithmic design; Bayesian inference; Monte Carlo methodology; Perfect simulation; Scalable methods for big data and big models; Stochastic differential equations.
m.pollock@warwick.ac.uk
Professor Patrick Rebeschini (Oxford)
Algorithms: message-passing; distributed, online, and stochastic optimization; bandits; boosting; Monte Carlo in high-dimension.
patrick.rebeschini@stats.ox.ac.uk
Algorithms: message-passing; distributed, online, and stochastic optimization; bandits; boosting; Monte Carlo in high-dimension.
patrick.rebeschini@stats.ox.ac.uk
Professor Gesine Reinert (Oxford)
Probabilistic and statistical methods for network analysis. Stein's method and the quantification of approximations.
reinert@stats.ox.ac.uk
Probabilistic and statistical methods for network analysis. Stein's method and the quantification of approximations.
reinert@stats.ox.ac.uk
Professor Christian Robert (Warwick)
Approximate Bayesian methods, aimed at complex and intractable likelihoods, towards producing manageable and convergent inferential solutions. Foundations of Bayesian testing and model choice, towards producing a more all-inclusive resolution compared with the Bayes solutions inspired from the Neyman-Pearson universe. Acceleration of MCMC methods, during and after simulation, by means of reparameterisation, coupling, Rao-Blackwellisation, and delayed acceptance.
C.A.M.Robert@warwick.ac.uk
Approximate Bayesian methods, aimed at complex and intractable likelihoods, towards producing manageable and convergent inferential solutions. Foundations of Bayesian testing and model choice, towards producing a more all-inclusive resolution compared with the Bayes solutions inspired from the Neyman-Pearson universe. Acceleration of MCMC methods, during and after simulation, by means of reparameterisation, coupling, Rao-Blackwellisation, and delayed acceptance.
C.A.M.Robert@warwick.ac.uk
Professor Gareth Roberts (Warwick)
I work on theory, methodology and applications of computational statistics, especially Markov chain Monte Carlo. Specific current interests include continuous time and non-reversible MCMC, adaptive methods in computational statistics, scaling limits and complexity of high-dimensional algorithms, and Bayesian inference for stochastic processes.
Gareth.O.Roberts@warwick.ac.uk
I work on theory, methodology and applications of computational statistics, especially Markov chain Monte Carlo. Specific current interests include continuous time and non-reversible MCMC, adaptive methods in computational statistics, scaling limits and complexity of high-dimensional algorithms, and Bayesian inference for stochastic processes.
Gareth.O.Roberts@warwick.ac.uk
Professor Stephen Roberts (Oxford)
Application of machine learning to huge astrophysical data sets, biodiversity monitoring and finance.
sjrob@robots.ox.ac.uk
Application of machine learning to huge astrophysical data sets, biodiversity monitoring and finance.
sjrob@robots.ox.ac.uk
Professor Judith Rousseau (Oxford)
Bayesian statistics ; Bayesian nonparametrics and high dimensional statistics ; Asymptotic properties of Bayesian procedures; measures of uncertainty; model selection; mixture and Hidden Markov models; Point processes; networks; statistical machine learning; computational statistics.
judith.rousseau@stats.ox.ac.uk
Bayesian statistics ; Bayesian nonparametrics and high dimensional statistics ; Asymptotic properties of Bayesian procedures; measures of uncertainty; model selection; mixture and Hidden Markov models; Point processes; networks; statistical machine learning; computational statistics.
judith.rousseau@stats.ox.ac.uk
Dr Richard Savage (Warwick)
My main research interest is statistical machine learning and its application to important problems in medicine, in particular early cancer detection. This principally involves the use of probabilistic methods for extracting scientific knowledge from large, potentially complex data-sets.
r.s.savage@warwick.ac.uk
My main research interest is statistical machine learning and its application to important problems in medicine, in particular early cancer detection. This principally involves the use of probabilistic methods for extracting scientific knowledge from large, potentially complex data-sets.
r.s.savage@warwick.ac.uk
Dr Dino Sejdinovic (Oxford)
Statistical machine learning. Kernel methods. Hypothesis testing with big data. Measures of association and multivariate interaction. Trade-offs between computational and statistical efficiency.
sejdinovic@stats.ox.ac.uk
Statistical machine learning. Kernel methods. Hypothesis testing with big data. Measures of association and multivariate interaction. Trade-offs between computational and statistical efficiency.
sejdinovic@stats.ox.ac.uk
Professor Jim Smith (Warwick)
High-dimensional environmental modelling. Multi-agent Bayesian decision theory in high dimensional models. High-dimensional business time series. Dynamic Bayes nets.
J.Q.Smith@warwick.ac.uk
High-dimensional environmental modelling. Multi-agent Bayesian decision theory in high dimensional models. High-dimensional business time series. Dynamic Bayes nets.
J.Q.Smith@warwick.ac.uk
Dr Dario Spanò (Warwick)
Mathematical population genetics. Bayesian non-parametric statistics. Combinatorial stochastic processes. Measure-valued processes.
D.Spano@warwick.ac.uk
Mathematical population genetics. Bayesian non-parametric statistics. Combinatorial stochastic processes. Measure-valued processes.
D.Spano@warwick.ac.uk
Dr Chris Spencer (Oxford)
Genetics and genomics. Bioinformatics, SNP typing and Statistical genetics.
chris.spencer@well.ox.ac.uk
Genetics and genomics. Bioinformatics, SNP typing and Statistical genetics.
chris.spencer@well.ox.ac.uk
Dr Simon Spencer (Warwick)
Bayesian inference, stochastic processes and applied probability, MCMC methods
S.E.F.Spencer@warwick.ac.uk
Bayesian inference, stochastic processes and applied probability, MCMC methods
S.E.F.Spencer@warwick.ac.uk
Professor Mark Steel (Warwick)
Bayesian statistics and econometrics. Modelling of skewness. Spatial statistics. Model uncertainty. Semi- and nonparametric Bayes.
M.F.Steel@warwick.ac.uk
Bayesian statistics and econometrics. Modelling of skewness. Spatial statistics. Model uncertainty. Semi- and nonparametric Bayes.
M.F.Steel@warwick.ac.uk
Dr Shahin Tavakoli (Warwick)
I am interested in both theory, methods, and applications of statistics. My area of expertise is Functional Data Analysis, but I am also interested in High-Dimensional Statistics, Stochastic Processes, Time Series Analysis, Multiple Testing, and Shrinkage Estimation. Recently, I've become increasingly interested in methodological developments driven by applications in Phonetics, Imaging, and Biophysics.
S.Tavakoli@warwick.ac.uk
I am interested in both theory, methods, and applications of statistics. My area of expertise is Functional Data Analysis, but I am also interested in High-Dimensional Statistics, Stochastic Processes, Time Series Analysis, Multiple Testing, and Shrinkage Estimation. Recently, I've become increasingly interested in methodological developments driven by applications in Phonetics, Imaging, and Biophysics.
S.Tavakoli@warwick.ac.uk
Professor Yee Whye Teh (Oxford)
Bayesian nonparametrics, probabilistic learning, deep learning.
y.w.teh@stats.ox.ac.uk
Bayesian nonparametrics, probabilistic learning, deep learning.
y.w.teh@stats.ox.ac.uk
Dr Sebastian Vollmer (Warwick)
Monte Carlo Methods, Stochastic Gradient Methods, Stochastic Processes
svollmer@turing.ac.uk
Monte Carlo Methods, Stochastic Gradient Methods, Stochastic Processes
svollmer@turing.ac.uk
Dr Jon Warren (Warwick)
Brownian motion. Local times. Branching processes. Dynamical systems.
J.Warren@warwick.ac.uk
Brownian motion. Local times. Branching processes. Dynamical systems.
J.Warren@warwick.ac.uk
