Career
- 2015-2016: Part III, focused on statistics and applied analysis
- 2012-2015: Undergraduate degrees in mathematics and physics
Research
Ferdia is a member of the Department of Applied Mathematics and Theoretical Physics. His current research interests lie at the interface of applied analysis and statistics.
Publications
Imaging With Equivariant Deep Learning: From unrolled network design to fully unsupervised learning
– IEEE Signal Processing Magazine
(2023)
40,
134
(DOI: 10.1109/msp.2022.3205430)
Dynamical systems' based neural networks
(2022)
Imaging with Equivariant Deep Learning
(2022)
Equivariant neural networks for inverse problems.
– Inverse problems
(2021)
37,
085006
(DOI: 10.1088/1361-6420/ac104f)
Structure-preserving deep learning
– European Journal of Applied Mathematics
(2021)
32,
888
(DOI: 10.1017/S0956792521000139)
Learning the Sampling Pattern for MRI
– IEEE transactions on medical imaging
(2020)
39,
4310
(DOI: 10.1109/TMI.2020.3017353)