Edwina Yeo

Doctoral Prize Postdoc, DPhil Candidate, Bsc Mathematics, Msc in Mathematical Modelling and Scientific Computing

Pronouns

She / Her

Status

Postgraduate Student

Contact form

https://sites.google.com/view/edwina-yeo-researcher/home

+44 1865 280603

Research groups

Oxford Centre for Industrial and Applied Mathematics

Address
Mathematical Institute
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG

Recent publications

Curvature in Biological Systems: Its quantification, Emergence and Implications Across the Scales.

Schamberger, B Roschger, A Ziege, R Anselme, K Amar, M Bykowski, M Castro, A Cipitria, A Coles, R Dimova, R Eder, M Ehrig, S Escudero, L Evans, M Fernandes, P Fratzl, P Geris, L Gierlinger, N Hannezo, E Iglič, A Kirkensgaard, J Kollmannsberger, P Kowalewska, Ł Kurniawan, N Papantoniou, I Pieuchot, L Pires, T Renner, L Sageman-Furnas, A Schröder-Turk, G Sengupta, A Sharma, V Tagua, A Tomba, C Trepat, X Waters, S Yeo, E Bidan, C Dunlop, J Advanced materials (Deerfield Beach, Fla.) e2206110- (03 Dec 2022)

Major / recent publications

Yeo et. al, Experimental and mathematical modelling of magnetically labelled mesenchymal stromal cell delivery, Royal Society Interface, 2021 https://royalsocietypublishing.org/doi/10.1098/rsif.2020.0558

Bidan et. al, Curvature in Biological Systems: Its quantification, emergence and implications across the scales, Accepted, Advanced Materials 2022.

Teaching

Tutor and TA for mathematics undergraduate courses including numerical solutions of differential equations, mathematical biology, applied complex variables.

Research interests

I am an applied mathematician interested in the intersection of continuum mechanics and mathematical biology. I specialise in the development of mathematical models for biological and biomedical fluid mechanics processes. I have developed mathematical models for biological systems in collaboration with researchers in the field of regenerative medicine and nanotechnology. Through formal model reduction on the mechanistic models I develop, I am also able to effectively parameterise these using experimental data. These models can then accurately predict the dynamics of complex biological systems.

I am currently an EPSRC Doctoral Prize Fellow, working on developing mean field models of magnetic dipoles in flow.