Research Topics

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Industrial Applications

A key research challenge of this research theme is to develop theoretical tools for the design and analysis of decentralized estimation and control schemes suitable for very large scale distributed hybrid dynamical systems with network connected sensors and actuators.  Such systems arise in urban transport systems, so-called smart-grid power systems, urban and rural water distribution systems, defence C4I systems, surveillance systems consisting of large swarms of possibly mobile sensors, industrial SCADA systems, and many other applications. 

Modern control and estimation techniques developed over the past 50 years provide efficient and practical solutions to a great range of small and medium scale multi-variable problems where centralized information structures prevail. Over the past 10 years important advances have been made in the understanding of information flows for decentralized control of dynamical systems and systems with non-classical information patterns.  There have also been significant advances in the application of optimization techniques for moving horizon control of large distributed systems with decentralized sensing and actuation. A major aim of these projects are to develop theoretical frameworks and robust design tools that address the challenges of estimator and controller design for very large distributed systems with networked sensors and actuators. 

Life Sciences Applications

ICT in Life Science is an inter-disciplinary field of study that focuses on complex interactions within a biological system.  This research area includes Systems Biology and Bioinformatics.  Systems Biology focus is on study, modelling, and predicting cells, tissue and organs properties, and discovering how biological systems work.  Bioinformatics focus is to understand complex life-science date, to develop new computational tools to make sense of biological, medical and health data.  Both these disciplines use techniques from the systems, signals and computer sciences, applied mathematics and statistics within the life sciences.

At the genomics level, the research challenges centre on the development of efficient string encoding and storage methods, genomic feature extraction and classification as well as new work in gene regulation pathway models.  Such work involves combining aspects of graph theory, dynamic systems and statistical modelling.  At the cellular level, researchers investigate techniques for the modelling and measurement of biological phenomena with a specific focus on the interactions between different levels of biological organisation.  New formulations of life-death processes have emerged along with tracking and path analysis for the analysis of the immune response of disease.