Margaret obtained a distinction in Part III of the Mathematical Tripos at the University of Cambridge, specialising in applied and computational analysis, which included a project on inverse problems with Carola Schoenlieb. This was followed by a PhD in mathematics at the University of Bath, supervised by Matthias Ehrhardt, where she worked on inverse problems arising from CT, MR, and PET imaging. Recently, she is a Computational Imaging Scientist in the Tomography and Imaging Group, where she manages the optimisation toolkit for the Core Imaging Library (CIL), an open-source, predominantly Python-based software package for tomography and other inverse problems.
Now she is the acting group leader for the inverse problems group and is looking forward to helping the group and its members grow and develop!
inverse problems, large-scale data, tomography, stochastic optimisation methods, generative models, deep learning for inverse problems