I am an Assistant Professor at the University of Groningen in the Computational and Numerical Mathematics group of the Bernoulli Institute. Previously, I was a Computational Mathematician in the Scientific Computing Department (SCD) of the UK's Science and Techonology Facilities Council (STFC). I completed my PhD in the Numerical Analysis group at the University of Oxford supervised by Prof. Yuji Nakatsukasa.
My research focusses on numerical linear algebra (NLA) and linear inverse problems. I work on randomization in NLA, iterative solvers for least squares problems, Krylov methods for inverse problems, and NLA for experiment design. I am also interested in the intersections between randomized and high-dimensional statistics. More broadly, I work on large-scale fundamental matrix problems in computing.
E. N. Epperly, M. Meier, Y. Nakatsukasa, Fast randomized least-squares solvers can be just as accurate and stable as classical direct solvers, arXiv:2406.03468, 2024
M. Meier, Y. Nakatsukasa, A. Townsend, and M. Webb, Are sketch-and-precondition least squares solvers numerically stable?, SIAM J. Matrix Anal. Appl., 45(2), 2024.
M. Meier, and Y. Nakatsukasa. Fast randomized numerical rank estimation for numerically low-rank matrices, Linear Algebra Appl., 686, 2024.
M. Meier and Y. Nakatsukasa, Randomized algorithms for Tikhonov regularization in linear least squares, arXiv:2203.07329, 2022.