Prof. Ruth Baker | Mathematical Institute

Prof. Ruth Baker

M.Math., D.Phil.

Status:

Academic Faculty

Professor of Applied Mathematics

Contact form

Personal website:

http://www.iamruthbaker.com

+44 1865 283893

ORCID iD:

https://orcid.org/0000-0002-6304-9333

Research groups:

Address

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

Recent Publications:

Chaste: Cancer, Heart and Soft Tissue Environment

Chaste: Cancer, Heart and Soft Tissue Environment
Bernabeu, M; Bowler, L; Bordas, R; Byrne, H; Bueno-Orovio, A; Carapella, V; Cardone-Noott, L; Maini, P; Mirams, G; Kursawe, J; McMillan, B; Baker, R; Cooper, F; Robinson, M; Pathmanathan, P; Pitt-Francis, J; Osborne, J; Rodriguez, B; Gavaghan, D; Spiteri, R; Cooper, J; Fletcher, A; Evans, B; Dutta, S; Hendrix, M
Journal of Open Source Software issue 47 volume 5 page 1848-1848 (13 March 2020)

Pakman: a modular, efficient and portable tool for approximate Bayesian inference

Pakman: a modular, efficient and portable tool for approximate Bayesian inference
Pak, T; Baker, R; Pitt-Francis, J
Journal of Open Source Software issue 47 volume 5 page 1716-1716 (7 March 2020)

Testing models of mRNA localization reveals robustness regulated by reducing transport between cells

Testing models of mRNA localization reveals robustness regulated by reducing transport between cells
Harrison, J; Parton, R; Davis, I; Baker, R
Biophysical Journal issue 11 volume 117 page P2154-2165 (3 December 2019)

Convergence of solutions in a mean-field model of go-or-grow type with reservation of sites for proliferation and cell cycle delay

Convergence of solutions in a mean-field model of go-or-grow type with reservation of sites for proliferation and cell cycle delay
Baker, R; Boldog, P; Rost, G
Progress in Industrial Mathematics at ECMI 2018 volume 30 page 381-387 (23 November 2019)

Accurate and efficient discretizations for stochastic models providing near agent-based spatial resolution at low computational cost

Accurate and efficient discretizations for stochastic models providing near agent-based spatial resolution at low computational cost
Fadai, N; Baker, R; Simpson, M
Journal of the Royal Society, Interface issue 159 volume 16 page 20190421- (31 October 2019)

Research interests:

My research focuses on developing and applying novel mathematical, computational and statistical methodologies and modelling frameworks for investigating developmental biology systems at the cell and tissue level. I develop biologically realistic models that, used in tandem with experimental investigations, can provide fundamental insights into key biological mechanisms. An important aspect of my work is therefore multidisciplinary collaboration with theoreticians, life scientists and clinicians both within Oxford and further afield.

I also play a key role in QBIOX (www.qbiox.ox.ac.uk), an MPLS-funded initiative to develop quantitative biology in Oxford.

Prizes, awards, and scholarships:

Royal Society Wolfson Research Merit Award 2017-2022
Leverhulme Research Fellowship 2017-2019
London Mathematical Society Whitehead Prize 2014

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