Data Science

Data Science is concerned with the analysis of both data and knowledge, including the way they are modelled, represented, and how they can influence reasoning. Such data may originate from complex systems, micro/nano structures, sensor arrays (such as within smart city environments), linguistic streams (such as social media feeds) or large scale biomedical data (such as from cell imaging, genomics, proteomics and metabolomics). This theme cuts across much of the research in the school, and includes novel approaches (such as chromatic technology) for monitoring and modelling real complex systems to yield operation information fault development; robust control for the systems with time delay; machine learning and data mining, including work on support vector machines, mathematical morphology, neural networks, and reinforcement learning; autonomous computer systems that are capable of self-interested action in dynamic, unpredictable environments in order to meet their design objectives; and the deep analysis of biological mass spectrometry data to characterise the protein and metabolite content of blood and tissue samples for disease understanding, early disease detection and the development of future therapies. The research on Logic and Computation also includes activities in database theory, ontology-based data access, and data integration.

More information on our activities that fall under Data Science Research can be found within the following thematic areas:

and encompass research in the areas of Argumentation, Knowledge Representation, Machine Learning, Verification and Signal Processing.

There is a high degree of synergy with research in this area across the school, and the recently formed Liverpool Big Data Network, which provides expertise in High Performance Computing and Big Data from across the University of Liverpool.