I have a BSc in mathematics and statistics from the University of Nottingham
and an MSc in computational and mathematical finance from the University of Oxford.
I'm a member of New College, Oxford.
I'm interested in the use of mathematics and computation to solve important,
practical problems. In particular mathematical modelling attempts to do this
by making the scientific method more rational and quantitative. I'm therefore
interested in all the technology of modelling and the associated mathematical
and computational challenges. More broadly I'm interested in the debate between
data-driven and hypothesis-driven science, particularly in the mathematical and
computational tools that power them. I'm also interested in the use of
visualisation to solve problems and communicate science.
10 week project. In collaboration with a computational biologist and an experimentalist at UCB, my academic supervisor
Charlotte Deane and I in the Proteomics Group (Oxford Department of Statistics) investigated the use of data-mining
methods (multilevel clustering) to find disease markers associated with auto-immune disease in big-data
(protein-protein interaction networks).
10 week project and DPhil. In collaboration with computational biologists at
Astrazeneca (Alderley Park) and immunologists at MedImmune (Cambridge) my academic
supervisors Helen Byrne, David Gavaghan and James Osborne and I in the Computational Biology Group
(Oxford Computer Science Department) are developing mathematical models to aid the development of
antibody cancer therapies. Antibodies are now engineered that bind to targets
(receptors) on tumour cells and incite immune cells to kill them. Such immunotherapies
now routinely treat previously untreatable cancers and are under intense development.
The aim of our modelling work is to quantify the impact of antibody design on therapeutic efficacy
(tumour cell killing) and to use mathematics and computation to suggest optimisations.