Research themes within the Mathematics and Statistics Research Group (MSRG)
The research themes of the MSRG are Mathematics, Statistics and Pedagogy. More specifically, the central focus is on applications in graph theory, mathematical modelling in the biosciences, applied statistical methods and mathematical education and e-assessment. The emphasis on real-world applied research aligns with the UWE Bristol Strategy 2030. Some particular topics of MSRG are given below.
The Group contributed to research and knowledge exchange (KE) culture at School level, e.g. it co-hosted the 64th annual British Applied Mathematics Colloquium (BAMC) at UWE Bristol (ca. 400 participants) and organised and supported the recent Data Science and Mathematics Research Showcase. The key contribution of the Group to research and KE culture at College level and beyond is its interdisciplinary approach to research, which, for example, adds value to interdisciplinary research projects.
The Group also contributes to EDI, e.g. a book devoted to a female pioneer in graph theory, Methods of Graph Decompositions, was published by Oxford University Press (July 2024).
Braess’ Paradox in transport networks
Represented by Dr Vadim Zverovich, Associate Professor.
Our research provides an extension of previous studies on Braess’ Paradox by considering arbitrary volume-delay functions.
Decision-support system for emergency response
Represented by Dr Vadim Zverovich, Associate Professor.
We developed an algorithm for finding the optimal routes for search and rescue teams in a building.
Diagnostic learning resources
Represented by Dr Rhys Gwynllyw, Associate Professor; Dr Karen Henderson, Associate Professor; Dr Emily Walsh, Senior Lecturer; Mr Basil Norbury, Senior Lecturer; and Dr Kevin Golden, Dean and Head of the School of Computing and Creative Technologies.
We have created diagnostic learning resources for several different student cohorts that provide mathematics support. Dewis has been used as the primary diagnostic tool and this provides additional feedback support in the form of signposting to learning materials based on areas that require attention.
Model reduction methods in systems biology
Represented by Dr Lloyd Bridge, Senior Lecturer in Mathematics.
Asymptotic analysis and hybrid asymptotic-numerical approaches help to reduce high-dimensional differential equation models of biological processes to provide new insights into the core mechanisms of interest.
Multiple domination and limited packings in graphs
Represented by Dr Vadim Zverovich, Associate Professor.
We developed an application of the probabilistic method to k-limited packings in general and to 2-packings in particular.
New statistical approaches
Represented by Dr Paul White, Associate Professor (Applied Statistics).
Stochastic simulation is an ideal tool for assessing the behaviour of existing and newly proposed statistical techniques and methods. Based on past successful PhD work, we will consider the development of new bespoke approaches in the development of new methodology.
Operations and maintenance in offshore wind farms
Represented by Dr Xiaodong Li, Lecturer.
The maintenance cost reduction is a key theme in order to make offshore wind power more competitive in the energy market.
Problem-based learning
Represented by Dr Vadim Zverovich, Associate Professor; Dr Jason Anquandah, Lecturer; Dr Xiaodong Li, Senior Lecturer; Tara Rasti, PhD student; Clemence Rhodes-Maquaire, PhD student; Dr Indunil Sikurajapathi, Lecturer; and Dr Laura de Vito, Senior Research Fellow.
This is a focus group on Problem-Based Learning (PBL). The purpose of such a group is to discuss PBL-related issues and opportunities to introduce PBL into our curriculum.
Receptor dynamics and mathematical pharmacology
Represented by Dr Lloyd Bridge, Senior Lecturer in Mathematics.
Mathematical models of cellular signalling dynamics are needed in order to understand and characterise ligand-receptor interactions using new experimental time-course data. Our models typically comprise nonlinear differential equations or agent-based models.
Robustness of statistical tests
Represented by Dr Ben Derrick, Lecturer.
This research explores and presents alternatives to statistical techniques to provide robust solutions.
Structured life course modelling approach
Represented by Dr Andrew Smith, Senior Lecturer in Statistics.
Identifying statistical models that represent the relationship between an exposure measured over an individual’s life course and a later health outcome. Interpreting such models requires model selection and post-selective inference.
Using technology enhanced learning to support the student experience
Represented by Dr Rhys Gwynllyw, Associate Professor and Dr Karen Henderson, Associate Professor.
We are interested in evaluating the effectiveness of using technology enhanced learning in the teaching of mathematics. This includes the use of e-assessment, technology-enhanced active learning spaces, audience-response systems.
Mathematics and Statistics Research Group (MSRG)
Delivering internationally excellent mathematics research, including real-world impact; develop research collaboration; apply its research to outstanding learning and generate income.
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