Research output per year
Research output per year
Personal profile
Research interests
Research
Sebastian is interested in:
- Solving linear ill-posed inverse problems
- Numerical linear algebra
- Large scale optimisation
- Machine learning approaches to inverse problems
Education
Sebastian graduated from the University of Bath with a first class honors Masters of Mathematics. His masters dissertation, titled "efficient priorconditioning for edge enhancement in imaging", involved the regularisation of discrete ill-posed linear inverse problems and employing Krylov subspace methods that adaptively define edge-enhancing encodings between iterates.
He is currently enrolled on the Integrated PhD Statistical Applied Mathematics, as part of the Statistical Applied Mathematics at Bath (SAMBa) EPSRC CDT. The topic of his PhD concerns how one may use machine learning approaches to solve inverse problems.
Education/Academic qualification
Master of Mathematics, Efficient priorconditioning for edge enhacement in imaging, University of Bath
Oct 2016 → Jul 2020
Award Date: 23 Jul 2020
Keywords
- Inverse Problems
- Optimisation
- Machine Learning
- Numerical Linear Algebra
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Research output
- 1 Article
-
Flexible Krylov Methods for Edge Enhancement in Imaging
Gazzola, S., Scott, S. & Spence, A., 18 Oct 2021, In: Journal of Imaging. 7, 10, 216.Research output: Contribution to journal › Article › peer-review
Open Access1 Citation (SciVal)