Supervisors

 

The following academic staff are potential supervisors for data science MSc and PhD projects. More details can be found on their individual web pages.

 

Machine Learning & Statistics

Vaishak Belle

Vaishak Belle Explainable AI, scalable probabilistic inference and learning, probabilistic programming, statistical relational learning, commonsense reasoning, automated planning, and unifying logic and probability more generally.

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Natalia Bochkina

Natalia Bochkina Bayesian nonparametric wavelet regression. Bayesian hierarchical modelling of genomics data.

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Miguel de Carvalho

Miguel de Carvalho Data visualization and graphical learning; Econometrics; Geometrical statistics; Medical diagnostic assessment; Statistical inferences for small-probability events; Statistics of extremes.

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Jonathan Gair

Jonathan Gair Big data in the physical sciences; analysis & exploitation of data from gravitational wave detectors; quantifying uncertainty in inference based on complex models; statistical emulation in the physical, biological & environmental sciences.

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Michael Gutmann

Michael Gutmann Efficient statistical learning, inference for stochastic dynamical systems, unsupervised deep learning, natural image statistics, computational biology.

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Vanda Inacio

Vanda Inacio Research interests: Bayesian statistics, Nonparametric Statistics, Biostatistics, Functional data analysis, and Statistical Computing.

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Ruth King

Ruth King Bayesian inference; Capture-recapture; Hidden (semi-)Markov models; Missing data; State-space models; Statistical ecology.

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Iain Murray

Iain Murray Bayesian statistics, approximate inference, Markov chain Monte Carlo, scientific data analysis.

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Ioannis Papastathopoulos

Ioannis Papastathopoulos Extreme Value Theory and Statistical Inference; Multivariate Analysis and Graphical Models; Spatial statistics; Environmental Science and Biostatistics.

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Guido Sanguinetti

Guido Sanguinetti Probabilistic modeling of biological systems, dynamics of regulatory networks, computational epigenetics, spatiotemporal systems.

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Amos Storkey - Co-director

Amos Storkey Structured machine learning & big data: Bayesian methods, Machine Learning Markets, learning representations & structure, deep learning, models for sequences & connections to neural computation. Applications in images, brain imaging, medicine & signal processing.

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Kartic Subr

Kartic Subr Analysis of Monte Carlo sampling, stochastic signal processing and numerical integration of high-dimensional discontinuous functions with applications in light transport simulation for computer graphics, image processing and computational photography.

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Charles Sutton - Director

Charles Sutton Machine learning, probabilistic models, approximate inference, deep learning. Applications to software engineering, programming languages, sustainable energy, & data mining.

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Chris Williams

Chris Williams Machine learning, image understanding, time series understanding, unsupervised learning, deep learning, Gaussian processes.

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Databases

Peter Buneman

Peter Buneman Databases: data models, query languages, semistructured data, data provenance, databases & programming languages. Programming languages: functional programming & type systems. Bioinformatics & scientific databases. Mathematical phylogeny.

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James Cheney

James Cheney Databases and data provenance. Programming languages and compilers. Generic programming. Logic and automated theorem proving. Compression and information theory. XML and related technologies.

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Wenfei Fan

Wenfei Fan Database theory and systems: big data, data quality, data integration, database security, distributed query processing, query languages, social networks, Web services and recommendation systems.

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Leonid Libkin

Leonid Libkin Databases: query languages, relational, XML, and graph data, constraints and design, data integration and exchange, incomplete information. Logic in computer science, finite model theory, automata theory.

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Andreas Pieris

Andreas Pieris Databases with emphasis on query languages, knowledge representation and reasoning, computational logic and its applications to computer science.

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Stratis Viglas

Stratis Viglas Just-in-time SQL compilation, heterogeneous storage, and distributed computing.

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Philip Wadler

Philip Wadler Integrating query and programming languages, XML, functional programming, web programming.

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Algorithms & Big Data

Pramod Bhatotia

Pramod Bhatotia Distributed systems, "Big Data" systems, cloud computing, and storage systems.

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Mary Cryan

Mary Cryan Algorithms, especially algorithms for counting and sampling. Random structures. Learning theory. Pseudorandom generators.

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Kousha Etessami

Kousha Etessami Algorithms and complexity theory, algorithmic game theory, equilibrium computation, analysis of probabilistic systems, Markov decision processes and stochastic games, analysis of infinite-state systems.

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Jacek Gondzio

Jacek Gondzio Optimization methods for linear, quadratic and nonlinear programming. Linear algebra techniques and sparse matrix factorisation methods for optimization. Very large optimization problems in telecommunications, energy and finance.

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Andreas Grothey

Andreas Grothey Stochastic Optimization. High Performance Computing. Applications to Energy, Finance and Telecommunications.

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Peter Richtarik

Peter Richtarik Design and analysis of optimization algorithms for big data. Randomized, parallel and distributed methods. Gradient descent, stochastic gradient descent and coordinate descent. Supercomputing. Optimization in machine learning. Applications in industry, engineering, astronomy, biology and finance.

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Unstructured Data & Applications

Shay Cohen

Shay Cohen Computational linguistics and machine learning, specifically structured prediction. Computational methods for reasoning about natural language and linguistic structure.

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Christophe Dubach

Christophe Dubach Machine-learning techniques for energy-efficient systems. Automated design processes. Software and hardware adaptivity.

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Maurice Fallon

Maurice Fallon Robotics. Probabilistic methods for localization, tracking and mapping. Applications to: speech source tracking, marine vehicle cooperative localization, and low-cost RGB-D localization.

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Vittorio Ferrari

Vittorio Ferrari Computer vision. Learning visual concepts.

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Bob Fisher

Bob Fisher Range image and 4D video analysis including 3D model acquisition, video capture and analysis of biological organisms, and iconic image analysis.

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Nigel Goddard

Nigel Goddard Applied machine learning in energy-related areas. End use energy demand. Energy efficiency in buildings.

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Sharon Goldwater

Sharon Goldwater Learning linguistic structure in humans and machines.

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Kenneth Heafield

Kenneth Heafield Machine translation. Algorithms for web-scale data. Scaling statistical models without compromising quality. Approximate dynamic programming for natural language inference problems.

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Timothy Hospedales

Timothy Hospedales Machine Learning: Lifelong, transfer and multi-task learning, active and curriculum learning. Computer Vision: Deep learning, vision and language, object, action and person recognition. Robot Learning: Business and financial analytics.

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Frank Keller

Frank Keller Probabilistic models of cognition, parsing, language production, language acquisition, language vision interface, eyetracking.

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Simon King

Simon King Text-to-speech synthesis. The use of articulatory information for speech synthesis and automatic speech recognition. Speech perception and production.

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Ewan Klein

Ewan Klein Computational approaches to natural language semantics, syntax, prosody and phonology. Spoken language processing. Communicating with mobile robots and embodied devices. The Semantic Web and ontologies. Open data.

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Mirella Lapata

Mirella Lapata Probabilistic learning. Natural language understanding and generation. Information extraction.

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Alex Lascarides

Alex Lascarides Computational semantics and pragmatics, discourse and dialogue processing, communication with non-verbal actions, machine learning models of action and decision making, learning strategies in highly complex games.

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Adam Lopez

Adam Lopez Statistical models for machine translation and language understanding, formal language theory, structured prediction, and algorithms.

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Christopher Lucas

Christopher Lucas Causal inference, generalization, & latent variable discovery by human learners and machines . Hierarchical and nonparametric Bayesian models for abstract learning and knowledge transfer.

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Walid Magdy

Walid Magdy Social Computing: social content analysis, political bias detection, and users' behavior prediction.
Information Retrieval: social search, patent search, evaluation metrics, Arabic IR, and CLIR.
Data Mining: text mining, classification, and sentiment analysis.

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Johanna Moore

Johanna Moore Computational linguistics: natural language generation, dialogue, and discourse. Intelligent systems for education. Personalised information presentation, multi-modal interaction, user modeling, and knowledge representation.

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Jon Oberlander

Jon Oberlander Automatic discourse generation diagrammatic reasoning and communication individual differences in interaction.

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Steve Renals

Steve Renals Speech technology, multimodal interaction, spoken language processing.

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Dave Robertson

Dave Robertson Design and deployment of multi-agent systems; large-scale, automated design and transformation of knowledge bases and problem solvers; agent-oriented software engineering.

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Michael Rovatsos

Michael Rovatsos Intelligent agents and multiagent systems: reasoning about interaction, multiagent planning, collaborative learning, combination of knowledge-based and game-theoretic techniques, social computing.

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Rik Sarkar

Rik Sarkar Distributed algorithms for processing spatial and location data, computational geometry and topology. Sensing and inference in mobile devices, sensor networks. Analysis of large networks. Distributed optimization.

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Hiroshi Shimodaira

Hiroshi Shimodaira Trainable lifelike conversational agents, Acoustic models for automatic speech recognition, Handwriting recognition.

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Ian Simpson

Ian Simpson Neuroregulatory genomics, computational biology, statistics &machine-learning. Molecular control of neural development &function in relation to cognition, learning &memory. Evolution &conservation of molecular regulatory processes. Analysis of high-throughput data-sets (genomic, meta-genomic, transcriptomic &proteomic).

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Mark Steedman

Mark Steedman Computational linguistics, artificial intelligence, formal grammar, semantics, spoken intonation, statistical parsing, spoken language processing, animated conversational agents, and computational musical analysis.

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Bonnie Webber

Bonnie Webber Computational models of discourse, statistical machine translation (SMT), semantics for SMT.

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Junichi Yamagishi

Junichi Yamagishi Speech information processing. Statistical speech synthesis. Machine learning, speech production, and linguistics.

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Security, Privacy, & Ethical Issues

David Aspinall

David Aspinall Applications of machine learning to cyber security, such as software and malware analysis, user interaction in security, authentication, trust and reputation. Software verification and theorem proving.

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Andrew Gordon

Andrew Gordon Computer security; programming languages and their semantics and logics; probabilistic programming for machine learning.

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Kami Vaniea

Kami Vaniea Usable security and privacy. Human Computer Interaction. Supporting decision making through feedback. Making security and privacy technologies easier to use by understanding how people interact with them.

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