I am a postdoctoral research associate in the Cambridge Image Analysis group at the Department of Applied Mathematics and Theoretical Physics at the University of Cambridge, where I completed my PhD (Structure-preserving machine learning for inverse problems) in 2021 under the supervision of prof. Carola-Bibiane Schönlieb and dr Matthias J. Ehrhardt.

Before that, I took Part III of the Mathematical Tripos in Cambridge, graduating with a distinction, and I studied mathematics and physics at the undergraduate level at the Radboud University in Nijmegen, graduating summa cum laude in both subjects.

My main research interest is in studying how to build principled (i.e. incorporating desired symmetries, robustness etc.) machine learning and deep learning approaches to solving ill-posed inverse problems, such as those which arise in medical image reconstruction (e.g. MRI and CT). Much of my work in this direction draws inspiration from structure-preserving numerical methods. Besides this I have a broad interest in applied mathematics in general.

Check out my Google Scholar page for an up to date list of my publications.

I can be reached at the email address below: