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Complex systems

Our research specialises in large scale systems, data analytics at scale, multi-criteria optimisation and human/social computation.

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Our research spans four key themes:

  • cybersecurity
  • social and mobile computing
  • parallel and distributed systems
  • multi-criteria optimisation and mathematical modelling.

Underpinning these key areas are issues of scale and complexity, with a particular emphasis on human/systems interaction. Most of the research is carried out in collaboration with colleagues internationally (in Europe, US, Singapore and Australia).

Our cybersecurity work covers aspects of information and mobile data security and location privacy, cyber risk in online social networks (eg malware propagation and analysis), security of industrial control systems (eg SCADA systems) and cloud security. This aspect of our work links in with a number of other Academic Schools, including Social Sciences, Mathematics and Business.

Our work in mobile and social computation covers aspects of machine classification and statistical modelling of online social behaviour, understanding human personality, studying interaction with smart phones, and data science-based approaches for assessing risk to human safety. This work has links with other Academic Schools, including Social Sciences and Psychology.

Our parallel and distributed systems work focuses on high performance and distributed systems, covering various aspects of large-scale distributed systems management and performance analysis (such as Edge and Social Clouds), personal 'Data Lakes' and scientific workflow systems.

There is also more fundamental work in numerical algorithms and mapping of these to graphics processing units (GPUs). This work closely aligns with efforts in multi-criteria optimisation and mathematical modelling, and has links with other Academic Schools, including Mathematics and Engineering.

The group manages the Social Data Science Lab and the Internet of Things Lab.

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Group members