Research groups

Algebra and Discrete Mathematics Group

Members: Peter Higgins, Vanni Noferini, David Penman, Chris Saker, Alexei Vernitski and Gerald Williams.

Members of our Algebra and Discrete Mathematics Group publish papers in discrete mathematics, including combinatorial and computational aspects of the subject. In particular, the group focuses on areas such as graph theory and group theory. Its members also conduct abstract study of:

  • languages (including some inspired by programming languages)
  • networks (including some inspired by biological networks)
  • semigroups (including some inspired by finite automata)
  • equations (including some inspired by arithmetical laws).

Results include both mathematical statements and algorithms for solving problems. The group also studies the computational complexity of the problems and the efficiency of the algorithms.

The group publishes in algebraic and computational journals that include Theoretical Computer Science and the International Journal of Algebra and Computation.

Mathematical Modelling and Data Analysis Group

Members: Chris Antonopoulos, Edward Codling, Hongsheng Dai, John Ford, Georgi Grahovski, Andrew Harrison, Haslifah Hashim, Berthold Lausen, Vanni Noferini, Aris Perperoglou, Abdel Salhi, Hadi Susanto, Xinan Yang, and Qingfu Zhang.

All members of the group are active researchers in various types of mathematical modelling and data analysis.

John Ford, Abdel Salhi and Qingfu Zhang are interested in optimisation techniques, including numerical and evolutionary approaches. Ford and Zhang are members of the Intelligent Systems group in the School of Computer Science and Electronic Engineering.

The research of our statisticians, Hongsheng Dai, Berthold Lausen and Aris Perperoglou, is in the fields of biostatistics, clinical and health trials, computational and mathematical statistics, probability and survival analysis.

Edward Codling's research is based on mathematical modelling (“bottom- up” modelling and analysis) and there is widespread need for such research across the biological and ecological sciences.

The research of Andrew Harrison is based on the analysis of large omic datasets (“top-down” modelling and analysis), a central subject in modern biological and ecological research. Much of this data is freely available from the public domain or data of collaborative clinical trials.

Chris Antonopoulos is interested in mathematical modelling, computational neuroscience, Hamiltonian systems, chaotic dynamics, in methods for discriminating between order and chaos in dynamical systems, in complex statistics and diffusion in lattices, and in complex networks and complex systems.