Computing Research Group
Imagine a vision of the future where computers and computing devices will be available naturally and unobtrusively anywhere, anytime, and by different means. The Computing Research Group conducts world leading multidisciplinary and cross-cutting research into new citizen-centric technologies for the access to, and for the provision of, applications and services which are more immersive, more intelligent, and more interactive in both the real and the virtual world. Current research areas address:
- Computational intelligence including perception and reasoning in relation to image interpretation
- Web based services for application areas such as socio-technical systems including eLearning communities and spaces, and digital identity web dynamics and web semantics
- Adaptable and dependable information systems for enterprise applications and decision support; knowledge engineering, onologies, data mining and business intelligence
- Mobile computing; virtualisation and cloud computing; ubiquitous computing and networking
and underpin the School's priority research themes in Security, Health Technologies, Energy and Environment (including Space), and Digital Society.
Computing research has a high international profile with major funding from EPSRC, the EU and through Knowledge Transfer Partnerships, the latter resulting in strong links with local industry. The group has attracted significant media interest. Research students and visitors from across the world are welcomed.
Computational Vision
Dr James Ferryman
Dr Hong Wei
Dr Oswaldo Cadenas
Research is concerned with the computational issues of perception and reasoning in relation to image interpretation. There is a present focus on automated CCTV analysis for security and threat assessment, biometrics, and segmentation and classification of remotely sensed LIght Detection And Ranging (LIDAR) data.
Socio-Technical Systems
Socio-technical research is about the intersection of society and digital technologies, which is rapidly changing with the growing presence of mobile devices and social media. There is a focus on Digital Identity (the persona projected across the internet); learning and competencies; and communities.
Knowledge Engineering and Data Mining
Dr Giuseppe Di Fatta
Dr Lily Sun
Theoretical and practical research on knowledge engineering and data mining is devoted to techniques and algorithms, including all areas of data integration and processing, knowledge acquisition, representation and discovery. It also focuses on their applications and case studies in industrial, life sciences and business sectors.
Data Mining and Knowledge Discovery in Databases (KDD)
- clustering, classification, frequent pattern mining, subgraph mining, statistical and Bayesian inference, machine learning, genetic algorithms, self-organising maps
- data integration, processing, analysis, exploration and visualisation
- mining and visualisation of high dimensional data
- parallel and distributed data mining algorithms, large and extreme scale data mining based on Gossip/Epidemic protocols
- data mining applications in: chemo-bioinformatics, computer networks and peer-to-peer (P2P) systems
Knowledge Engineering
- complex systems design for large organisations to SME setting
- requirements engineering to ensure enterprise agility and efficiency
- knowledge representation through Ontological methods for intelligent information retrieval
- business intelligence and profiling for personalisation and information provision to support decision making
- service-oriented design for supply chain management and customer relationship management.
Computational Science
Research in computational science includes novel and emergent systems and architectures, parallel and distributed computing, cloud computing, mathematical modelling, scalable algorithms, middleware to support parallel and distributed applications.