Department of Computer Science

Data Science and Machine Learning


Data Science generates actionable knowledge from any kind of data. It covers the full pipeline from collecting, preparing, and storing the data, to analysing it, presenting the results, and turning them into actions. Machine Learning provides the essential bits in the middle of this pipeline, the algorithms that analyse the data and produce patterns and predictions.

Members (academic staff or PhD students):

Academic staff: 
Damir AzharMichael BarleyRemco BouckaertGill DobbieYun Sing KohSebastian Link,Bernhard Pfahringer (coordinator), Patricia RiddleJim WarrenIan WatsonGeorgy Gimel'farbPatrice Delmas

PhD students:

Ian Wong, Alex Penga, Diana Prado, Monica Bian, Robert Anderson,Danah Algawiaz

More information:

Centre for Computational Evolution (CCE), hosted at the Department of Computer Science, was set up to promote collaborations in computational biology research. CCE brings together researchers who share an interest in developing software tools and computational models for understanding evolution and molecular ecology from genes to genomes. This approach spans fields as diverse as evolutionary biology, epidemiology, linguistics, culture, ecology and the origin of life.