Foundations

The Foundations of data science lie in methodology for the analysis, interpretation and organisation of complex data. Our schools of Mathematics and Computer Science carry out world-class research in computational statistics, machine learning, visual computing, advanced interfaces and information management. Another important area of data science research is around confidentiality and privacy, which are a particular focus of our the Cathie Marsh Institute for Social Research. Underpinning these developments is the requirement for powerful, scalable and reliable algorithms and architectures. 

ALAN TURING INT 1

Numerical Analysis and Scientific Computing

Interested in the study of algorithms for the problems of continuous mathematics, and in the numerical simulation of physical processes.

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ARTHUR LEWIS EX 10

Confidentiality and Privacy (CAPRI)

The interdisciplinary Confidentiality and Privacy Research Group (CAPRI) comprises academics working in statistics, social science, social policy, computer science and law.

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Machine Learning and Optimisation

World-leading research into a wide range of techniques and applications of machine learning, optimisation, data mining, probabilistic modelling, pattern recognition and machine perception.

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Information Management

Looking at the design, development and use of data & knowledge management systems, how data can be accessed & visualised, and how users interact with the web and how the web interacts with them.

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Statistics and its Applications

Research is carried out in various areas of statistics, ranging from theoretical studies to applied research.

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Advanced Processor Technolgies

SpiNNaker is a novel computer architecture inspired by the working of the human brain. A SpiNNaker machine is a massively parallel computing platform, targeted towards three main areas of research.

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