Executive Committee

 

The CDT's Executive Committee provides strategic direction, leadership, and daily management for the CDT in Data Science.

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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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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Peter Buneman

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

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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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Adam Lopez

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

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Sebastian Maneth

Sebastian Maneth Databases, especially text and XML. Data compression. Indexing. Query optimization.

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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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Chris Williams

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

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Sally Galloway - CDT Administrator

Sally Galloway

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Neil Heatley - CDT Manager

Neil Heatley

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David Richardson - Business Development Executive

David Richardson Startup & Spinout Companies, Technology Licensing, Consultancy, Collaborative Research, Industry Studentships

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