Computer Science research
We focus on research that has the potential to have a significant impact on the computational understanding and engineering of complex systems. Our research facilitates biomedical innovations that improve the quality of life for many people. The research we conduct paves the way for world leading software engineering innovations that improve the security, reliability and quality of computing devices and services used in industry.
Our research themes
We use computational modelling and analysis to understand how neural systems work and to design engineering solutions for biomedical problems that involve abnormal or lacking neural control.
We develop and analyse evolutionary systems to advance understanding of natural and artificial evolutionary processes and their capacity to generate increasingly intelligent behaviours.
Theme Lead: Dr Alastair Channon
Theme Members: Professor Peter Andras, Dr Elizabeth Aston, Dr James Borg, Dr Charles Day, Dr Theocharis Kyriacou, Dr Adam Stanton
We work on the development and application of machine learning and computational intelligence methods to address biomedical and engineering problems characterised by large volumes of complex data.
Research areas: complex systems, computational systems, knowledge modelling, human-computer interaction (HCI), user-centred design (UCD), ‘big data’ analytics, e-Learning and biological system design. We also have research interests in computer vision, cultural informatics, wearable systems and health technologies.
Theme Lead: Dr Sandra Woolley
Theme Members: Professor P Andras, Professor P Brereton, Professor B Kitchenham, Mr S Linkman, Dr G Misirli, Dr T Neligwa, Dr M Ortolani, Professor F Polack, Dr E de Quincey, Dr G Rugg, Dr M Turner, Professor Z Fan, Dr B Mandal