About me
I am a Hooke Fellow in the Mathematical Institute at the University of Oxford. My research interests include large scale numerical linear algebra (theory and applications), data assimilation, and treatment of covariance matrices. Alongside my research I’m interested in outreach and scientific crafting. Contact me at tabeart[at]maths[.]ox[.]ac[.]uk
News
I’ve just started a Hooke Fellowship in Oxford!
Successful grant funding from UNA Europa - Seed Funding DIGITALIZED! for the research project “Tensor-based Optimal Control approaches for Deep learning - TOC4Deep” Find out more here. See the website for information on events, and videos from past workshop talks.
I co-organised a workshop in April 2022 in Edinburgh on Recent Advances in Numerical Linear Algebra: Talks are on the website if you weren’t able to join us in person https://www.icms.org.uk/workshops/2022/recent-advances-numerical-linear-algebra-pdes-optimization-and-data-assimilation
Work and education history
October 2022 - Present: Fulford Non-Stipediary Fellow at Somerville College
September 2022 - Present: Hooke Fellow in the Mathematical Institute at the University of Oxford in the Numerical Analysis group.
2019 - August 2022: PDRA in the School of Mathematics at The University of Edinburgh working with Dr John W. Pearson
Spring 2020: Semester Postdoctoral Fellow at the Institute for Computational and Experimental Research in Mathematics at Brown University
2016 - 2019: PhD at the University of Reading with Professor Sarah Dance, Dr Amos Lawless, Professor Nancy Nichols and Dr Joanne Waller. Read my thesis here
2015 - 2016: MRes at Imperial College, London and University of Reading as part of the Mathematics of Planet Earth Centre for Doctoral Training
2011 - 2015: MMath at the University of Bath with Study Year Abroad at Université Joseph Fourier (now Université Grenoble Alpes)
Some recent papers
Stein-based preconditioners for weak-constraint 4D-var
Davide Palitta and Jemima M. Tabeart
Model Reduction of Linear Dynamical Systems via Balancing for Bayesian Inference
Elizabeth Qian, Jemima M. Tabeart, Christopher Beattie, Serkan Gugercin, Jiahua Jiang, Peter R. Kramer and Akil Narayan
Saddle point preconditioners for weak-constraint 4D-Var
Jemima M Tabeart and John W Pearson
The conditioning of least squares problems in preconditioned variational data assimilation
Jemima M Tabeart, Sarah L Dance, Amos S Lawless, Nancy K Nichols, Joanne A Waller
The impact of using reconditioned correlated observation‐error covariance matrices in the Met Office 1D‐Var system
Jemima M Tabeart, Sarah L Dance, Amos S Lawless, Stefano Migliorini, Nancy K Nichols, Fiona Smith, Joanne A Waller
Improving the condition number of estimated covariance matrices
Jemima M Tabeart, Sarah L Dance, Amos S Lawless, Nancy K Nichols, Joanne A Waller
The conditioning of least‐squares problems in variational data assimilation
Jemima M Tabeart, Sarah L Dance, Stephen A Haben, Amos S Lawless, Nancy K Nichols, Joanne A Waller
Other activities
I’m a co-organiser of the Communications in Numerical Linear Algebra series: find out more at our website or catch up on previous talks on our Youtube channel
Watch me present a recent pre-print
Follow me on Twitter @jemimatabeart for updates and photos of my crafting efforts
Since moving to Scotland I’ve started Munro bagging - my latest stats are here!
