At the School of Science and Technology, our research typically arises through the practical need to solve problems across 'real world' domains including medical imaging, networks and telecommunications, and robotics.
Many of these problems can be seen as tasks in mathematical modelling and optimization, using a variety of techniques. Our mathematical research blends seamlessly into work in areas such as algorithm design, learning theory and complexity theory being carried out in the Software Engineering and Algorithms Laboratory.
Within our team, there is also considerable strength in image and signal processing, typically applied to biomedical domains. We are particularly interested in the solution of inverse problems, and the application of this within clinical engineering. Finally, we have a significant interest in various logical and algebraic domains, including graph theory, quantum information theory, specialised logics for reasoning about states and ways in which algebraic manipulations facilitate the visualisation of complexity.