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Theoretical Foundations

Theoretical foundations

Deriving useful information from Big Data requires the development of increasingly sophisticated methods of mathematical and statistical analysis and the design of efficient algorithms. Research in this theme ranges from the development of statistical methodologies to extract meaningful information from Big Data, in particular, high dimensional data, to machine learning and the study of theoretical computer science.

Theme champions

Professor of Statistics, Statistical Laboratory, University of Cambridge
Teaching Fellow, St John's College

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