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Foundations of Data Science

Foundations of Data Science Theme Lead Dr Stefan Siegert

The Foundations of Data Science lie in methodology for the analysis, interpretation and organisation of complex data. Our academic expertise covers a wide range of topics such as data analytics, machine learning and artificial intelligence, statistical science, causal inference, optimisation, uncertainty quantification, dynamic modelling and simulation, complex systems and network analysis.

Technical work in machine learning and artificial intelligence is complemented by work on the philosophy of AI, and the extent to which conceptual and ethical assumptions are built into algorithms.

To get involved and find out more about the work of this research theme contact Stefan Siegert