Research Areas
The Department is organised into eight sections, which serve both an administrative function as well as reflecting common research interests and collaboration between members. The sections thus indicate the research focus of the Department. Sections also provide a support environment for research students, and organise seminars and workshops. Senior academics often work with junior staff to formulate research proposals and help to promote their external visibility by involving them in conference organisation, suggesting their names for seminars and invited talks etc.
The main research focus in Computational Bioinformatics is on the use of Inductive Logic programming, together with vector machine learning for Bioinformatic applications such as identification of toxins which inhibit enzymes in metabolic networks, prediction of 3 dimensional structure of molecules in biochemical reactions for drug development and the missing functions within metabolic and gene expression networks. Main interdisciplinary collaborations are via the College Centre for Bioinformatics.
The main research focus is on optimisation of performance, productivity and power consumption in designing hardware/software systems. The work includes theory and practice of custom instruction sets, hardware accelerators (e.g. based on FPGAs), static and dynamic architecture and code optimisation, as well as dynamic code generation. The section has strong links with industry and collaborative projects with the EE Department.
The DSE section combines sound, rigorous and formal software engineering approaches with practical techniques to build tools for the design, analysis and implementation of complex software systems, with particular interest on those that are distributed, pervasive and/or adaptive. Research topics include software modelling and analysis, requirements engineering, policy-based security and systems management, autonomic computing, language semantics for distributed programming, and data and knowledge engineering for heterogeneous databases and sensor networks. The section is involved in collaborative inter-disciplinary projects related to systems biology and healthcare.
The HPI section focuses on developing sophisticated mathematically-based methods and advanced software technologies to bridge the gap between challenging e-Science applications and the complex computing platforms (distributed resources, the Grid) required to support them. The HPI section works on performance modelling and engineering to provide quantitative understanding of complex systems to provide effective scheduling of resources, Web Services and component software technologies and intelligent Grid middleware to provide software environments to support the advanced application of these methods.
The research spans theoretical studies of logical systems and their computational properties, automated reasoning techniques, multi-agent system technologies, cognitive robotics, knowledge representation form alisms, and applications. There is a particular focus on abductive reasoning and machine learning, and on logics of time, action, and change, agent communication, agent and robot programming languages and organisational structures. The section is involved in collaborative international projects relating to multi-agent systems, web services, business rules and procedures, as well as trust and security in virtual organisations. Several members of the section are working on applications in bioinformatics and systems biology.
The QUADS section integrates effort in algorithm and software design to offer state-of-the-art quantitative and decision analysis methodology for a wide range of dynamical systems in def ence, engineering, economics, finance, infrastructure planning, energy, environment and earth and life sciences. This integration is achieved th rough the creation of novel algorithmic and semantic foundations and their transfer into frameworks and tools for quantitative analysis and decision systems. Research topics include data mining and knowledge discovery, games, optimization, uncertainty, risk and safety, and security and information flow. The section is involved in collaborative and interdisciplinary projects in grid-based informatics, stochastic and robust optimisatation within the context of uncertainty and risk.
The research focus includes programming language types and concurrency issues; analysis and verification of programs for correctness, efficiency and security of code; theory relating to distributed processes and data including reasoning about updating XML-based data and structures and fundamental models of dynamic web data. There is also work on new paradigms of computation which includes exact computation, complex systems and quantum computation.
The VIP group works on medical image computing, perceptual intelligence and ubiquitous sensing with a focus on biomedical applications. They develop methods and tools which make use of novel vision and image processing, virtual and augmented reality, biomechanical modelling, machine learning and Bayesian inferencing. There are strong links with the Institute for Biomedical Engineering and the Medical School.
