Research

This talk is broadly based on our paper Fast randomized least squares sovlers can be just as accurate and stable as classical direct solvers. I gave the talk in the Numerical Analysis and Scientific Computing Seminar at the University of Manchester.

This talk is broadly based on our paper Are sketch-and-precondition LS solvers numerically stable?, but includes some more figures on stability of various algorithms. I gave the talk at SIAM LA24 in Ilse Ipsen's and Arvind Saibaba's minisymposium.

These are extended slides from a 40-minute invited talk at Bath-RAL Numerical Analysis Day on the Are sketch-and-precondition LS solvers numerically stable? work.

This is an overview of most of my early PhD projects applied to linear inverse problems.

Slides from a talk I gave online at SIAM MDS22 on the preprint Randomized algorithms for Tikhonov regularization in linear least squares.

The Oxbridge Applied Mathematics Meeting is a friendly competition between the Oxford and Cambridge applied mathematics groups, where students give talks and the winner takes home a 'wooly owl'. I gave an introductory talk on numerical rank estimation based on the paper Fast randomized numerical rank estimation for numerically low-rank matrices.

Slides of my first talk as a PhD student on my MSc project Fast Randomized Numerical Rank Estimation.