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Dr Silvio Fanzon

Lecturer in Applied Mathematics

Faculty and Department

  • Faculty of Science and Engineering
  • School of Natural Sciences

Qualifications

  • BSc (Sapienza University of Rome)
  • MSc (Sapienza University of Rome)
  • PhD / DPhil (University of Sussex)

Summary

I am a Lecturer in Applied Mathematics at the University of Hull, with a research and teaching role.

My research is at the interface of Inverse Problems, Optimization and PDEs. I have also experience in Optimal Transport, Calculus of Variations, Measure Theory and Numerical analysis in infinite-dimensional spaces. I am interested in applications to Materials Science, Mathematical Imaging, and Machine Learning.

I have taught a diverse range of courses in the areas of Analysis, Geometry, Probability, Statistics and Numerical Analysis, at both the Undergraduate and Master levels.

If you are interested in collaboration or supervision opportunities, please contact me at

S.Fanzon@hull.ac.uk

For updated news and more details see my website

www.silviofanzon.com

This year I am teaching:

Numbers, Sequences & Series

Differential Geometry & Topology

Statistical Models

For a full list, see

silviofanzon.com/teaching

Recent outputs

View more outputs

Journal Article

Asymptotic linear convergence of fully-corrective generalized conditional gradient methods

Bredies, K., Carioni, M., Fanzon, S., & Walter, D. (2023). Asymptotic linear convergence of fully-corrective generalized conditional gradient methods. Mathematical Programming, https://doi.org/10.1007/s10107-023-01975-z

A superposition principle for the inhomogeneous continuity equation with Hellinger–Kantorovich-regular coefficients

Bredies, K., Carioni, M., & Fanzon, S. (2022). A superposition principle for the inhomogeneous continuity equation with Hellinger–Kantorovich-regular coefficients. Communications in Partial Differential Equations, 47(10), 2023-2069. https://doi.org/10.1080/03605302.2022.2109172

A Generalized Conditional Gradient Method for Dynamic Inverse Problems with Optimal Transport Regularization

Bredies, K., Carioni, M., Fanzon, S., & Romero, F. (2022). A Generalized Conditional Gradient Method for Dynamic Inverse Problems with Optimal Transport Regularization. Foundations of Computational Mathematics, https://doi.org/10.1007/s10208-022-09561-z

On the extremal points of the ball of the Benamou–Brenier energy

Bredies, K., Carioni, M., Fanzon, S., & Romero, F. (2021). On the extremal points of the ball of the Benamou–Brenier energy. Bulletin of the London Mathematical Society, 53(5), 1436-1452. https://doi.org/10.1112/blms.12509

An optimal transport approach for solving dynamic inverse problems in spaces of measures

Bredies, K., & Fanzon, S. (2020). An optimal transport approach for solving dynamic inverse problems in spaces of measures. ESAIM: Mathematical Modelling and Numerical Analysis, 54(6), 2351-2380. https://doi.org/10.1051/m2an/2020056

Research interests

Main Areas:

Inverse Problems

Optimization

PDEs

Sub-Areas:

Calculus of Variations

Optimal Transport

Measure Theory

Regularity Theory

Gradient methods

Primal-dual methods

Applications:

Mathematical Imaging

Materials Science

Machine Learning

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