Hello there!
View the code on GitHub.
I am PhD candidate in the Mathematics of Imaging & AI research group under the supervision of dr. José A. Iglesias and prof. dr. Christoph Brune.
I have been working on inverse problems with PDE constraints and sparse optimization. My research focuses on translating and applying known sparse optimization methods to a broad range of inverse problems, where geometric priors are encoded through PDE constraints. Check out my list of Publications.
View the code on GitHub.
I am particularly interested in turning mathematical models into methods that are actually competitive in practice, and in understanding why effective heuristic methods are mathematically sound, especially in areas such as computer graphics and geometry processing. My technical work spans Python and C++ for finite element methods, optimization, and large-scale numerical computation.
View the code on GitHub.
I am currently expanding my expertise towards computational geometry and simulation-driven design, with the goal of contributing to the development of next-generation engineering and design tools.
I will be available for new opportunities starting October 2026. I am interested in junior or internship positions in R&D, as well as PostDoc positions with possible industry collaboration. I am open to relocation.
View the code on GitHub.
View the code on GitHub.
View the code on GitHub.
Away from the desk
Climbing, hiking, table tennis & chess
Publications
Towards sparse optimization over convex loops: Equivalence of Square Root Velocity distance and Wasserstein-Fisher-Rao
Joint work with: José A. Iglesias (University of Twente)
Conditional Gradients for Total Variation regularization with PDE constraints: a graph cuts approach
Joint work with: José A. Iglesias (University of Twente) and Daniel Walter (HU Berlin)
Linear convergence of a one-cut conditional gradient method for total variation regularization
Joint work with: José A. Iglesias (University of Twente) and Daniel Walter (HU Berlin)
Activities
Sparse optimization on length measures towards PDE constrained problems
I will advertise my new paper during the sparse approximation minisymposium at Curves and Surfaces 2026.
Towards sparse optimization on length measures
I will advertise my new paper during the Optimization on Measures minisymposium at SIAM Optimization 2026.
New Mathematical Methods in Geometry Processing
Lecturers: Justin Solomon, Gabriele Steidl, Niloy Mitra, Maks Ovsjanikov. More info here.
Warsaw Summer School on Evolutionary PDEs
Lecturers: Massimiliano Morini, Xavier Ros Oton, Julio Daniel Rossi. More info here.
University of Houston
Two-months research visit in the Mathematics department of UH to foster a collaboration with dr. Nicolas Charon.
Mathematics and Machine Learning for Image Analysis
Lecturers: Alessandro Foi, Ulugbek Kamilov, Jean-Christophe Pesquet, Luca Ratti, Lorenzo Rosasco, Michaël Unser. More info here.
Sparse optimization for discretized PDE-constrained problems with total variation regularization
Contributed talk within the Calculus of Variation workshop 2023 in the beautiful island of Schiermonnikoog.
Spring School on Geometric Methods in Data Science
Selected Speakers: Jurgen Jost, Althea Monod, Emil Saucan. More info here.
Courses and support
Vector Calculus for Electrical Engineering
Vector Calculus for Mechanical Engineering
Calculus 1 for Computer Science
Vector Calculus for Electrical Engineering
Analysis 3 for Applied Mathematics
Linear Algebra for Mechanical Engineering
Linear Algebra for Computer Science
Analysis 3 for Applied Mathematics
Linear Algebra for Computer Science
Notes
Introduction to TikZ: a graphic library in Latex
An illustrated introduction to TikZ and PGF for mathematical graphics.
A Taxonomy of Deep Learning Methods in Geometry Processing
A survey of contemporary deep learning methods in geometry processing.
Curriculum vitae
Here you can find my full cv (last update: August 2026).
Education
- Ph.D in Applied Mathematics, University of Twente, 2026 (expected)
- M.Sc. in Mathematics, Utrecht University, 2022
- B.Sc. in Mathematics, University of Trento, 2019
Technical skills
- Languages: Italian (Mothertongue), English (C1/C2), Spanish (A2)
- Coding languages: Python, Cpp, Julia, Matlab, HTML (in order of proficiency: high -> basic)
- Softwares for Simulations & Design: Ansys, Blender, Paraview
- Other tools: git
- Familiarity with agile methodologies
Certificates and Other Courses
- Computer Graphics, (online edX) (To be completed)
- Software engineering essentials (online edX) (To be completed)
- Engineering Design and Simulations (online edX) (To be completed)
- New Mathematical Methods in Geometry Processing, (in loco) University of Bonn (2026)
- Introduction to Cpp, (in loco) University of Twente (2025)
- Mathematics and Machine Learning for Image Analysis, (in loco) University of Bologna (2024)