Members of the team are engaged in interdisciplinary research in applied mathematics with applications in a number of interlinking industries.
Research is an important activity, ensuring the vitality and health of our academic subjects, and underpins the teaching of our courses.
Members of the mathematics team are engaged in interdisciplinary research in applied mathematics with applications to biomedical, health and life sciences, engineering, computing and industry, specifically in the following areas of mathematics:
- biomathematics, bioinformatics and computational biology
- statistical learning theory and applications
- industrial mathematics
- mathematical modelling and numerical analysis
- quantum information science
- graph theory and combinatorics
- deep learning and biomedical image analysis
The research of the Biomathematics and Bioinformatics group focusses on the development of novel mathematical and statistical approaches for analysis of data emerging from various disciplines, including Biosciences. It aligns with the Allied Health Professions, Dentistry, Nursing and Pharmacy subject area and Health and Wellbeing strategic research theme.
- Prof Chuzhanova's research interests include in silico modelling of mechanisms of mutations underlying inherited disease and cancer, based upon computational statistics and DNA complexity measures. She is particularly interested in the role of repetitive sequences, epigenetic factors and 3D architecture of the human genome in mutagenesis.
- Dr Crofts' research is in computational and applied mathematics with strong interests in computational neuroscience. In particular, his current research focusses on developing new mathematical approaches that combine techniques from network science, data-mining and dynamical systems in order to understand complex self-organising systems such as the brain.
- Dr Nelson's research is primarily in the area of Mathematical Biology, with particular focus on biomechanical models and models of complex many-cell systems. Applications to date include morphogenesis of soft tissues, tissue engineering, and sexually-transmitted infections. Current projects include modelling spatial aspects of the anti-inflammatory response via both partial differential equations and cellular automata models, and using techniques from network science and dynamical systems theory to elucidate the mechanisms underlying certain neurological conditions.
The Computation and Simulation research group is an interdisciplinary team of applied mathematicians and engineers. Within applied mathematics, the focus of the group is on designing bespoke numerical tools for problems arising in both engineering and the natural sciences, often motivated by demand from industry end-users. The group has expertise in boundary element methods, equivalent source methods, finite difference methods, finite element methods and ray/particle methods including Dynamical Energy Analysis (DEA). A major focus of recent work has been on high-frequency wave modelling of sound and vibration in built-up structures using DEA, with applications in the transport sector.
- Dr Chappell's research interests surround mathematical modelling and numerical analysis with industrial applications. Areas of current interest include time-dependent wave propagation problems, boundary integral and boundary element methods, convolution quadrature methods, inverse problems, fluid-structure interaction problems, high frequency wave modelling in complex industrial and engineering structures, numerical methods for phase space flow equations, uncertainty modelling and multi-scale methods. In 2016, Dr Chappell was awarded the Vice Chancellor’s Outstanding Researcher Award (early career). His research is aligned with the Engineering subject area.
- Dr Bajars’ research interests surround areas in Applied and Computational Mathematics. The main focus encompasses the development of new integral equation methods for modelling uncertain and high frequency vibrational energy distributions in complex built-up structures. His research is aligned with the Engineering subject area.
Contact for Computation and Simulation group: Associate Prof David Chappell.
The research of Mathematical Aspects of Computer Science group focusses on the developing mathematical and statistical foundation for a range of computational techniques and approaches. It aligns with the Computing and Informatics subject area.
- Quantum computing research, undertaken by Dr Wilmott, is conducted in entanglement, quantum computing, quantum cryptography, and quantum error-correction – all of which drive new work in the area of quantum technologies. Our investigations are based on innovative, award-winning research – an example of which relates to our novel approach to optimal quantum circuit construction for high performance, miniaturisation and scalability, and makes great use of mathematical aspects from combinatorics and number theory.
- The focus of Dr Shahtahmassebi's research is on the development and application of methodology of Statistical Learning Theory and Bayesian Inference to modelling non-Gaussian and non-linear data. Application areas include multispectral image analysis with application to art history and conservation and quality control (defect or crack detection); remote sensing studies (land cover information extraction from satellite images); modelling high latitude ionosphere plasma structure in atmosphere.
- Dr Hetherington’s research interests include graph theory and combinatorics, in particular colourings and list-colourings.
- Dr McCollin works on identifying latent structure within systems reliability data. He attempts to identify structure on the basis of physical relationships and systems structure. Any complex system with many failure times where previous analysis has identified the exponential distribution as fitting the data is therefore a candidate for further analysis. Current work involves modelling with Lévy processes. He is currently applying the methods to dementia data.
Dr Giannakidis’s research lies in developing novel techniques for the intelligent processing of visual information, with a particular focus on biomedical applications. His research includes using machine learning and deep learning techniques for extracting clinically useful information from cardiovascular MRI datasets. Another main research area of his is in diffusion tensor MRI. His research is linked to Allied Health Professions, Dentistry, Nursing and Pharmacy subject area.