Curriculum vitae

Education

1. 2024 — 2027 (expected)
   Ph.D. in Computational Mathematics, Learning, and Data Science
   Università di Pavia · Pavia, Italy

   Mathematically certified deep learning algorithms for inverse problems governed by PDEs, with application to personalised treatment plans in oncology. Marie Skłodowska-Curie Doctoral Fellow, IN-DEEP European Doctoral Network. Supervisors: A. Reali, G. Sangalli (Pavia), C. Canuto (Politecnico di Torino).

2. 2021 — 2024
   M.Sc. in Computational Science and Engineering
   École Polytechnique Fédérale de Lausanne (EPFL) · Lausanne, Switzerland

   GPA 5.96/6.00. Thesis: Preconditioned Low-Rank Riemannian Optimization for Multiterm Linear Matrix Equations (advisors D. Kressner, L. Robol). Prix Douchet and Best Master Average Grade Prize 2024.

   Thesis (PDF)
3. 2018 — 2021
   B.Sc. in Mathematics
   Università di Pisa · Pisa, Italy

   110/110 cum laude. Thesis: Low-rank numerical methods for the Sylvester equation (advisor D. A. Bini).

   Thesis (PDF)Code

Languages

• ItalianNative
• EnglishProficient (C2)Cambridge English: Advanced, grade A
• SpanishIntermediate

Research experience

1. Oct 2026 — Jan 2027Upcoming
   Research stay
   Tecnalia Research & Innovation · Bilbao, Spain

   With J. Del Ser. Explainable AI and differentiable machine learning frameworks for interpretable tumor growth modelling: patient-specific prediction, parameter estimation and uncertainty quantification.

2. Sep 2026 — Oct 2026Ongoing
   Research stay
   Università di Firenze, Department of Mathematics and Computer Science “U. Dini” · Florence, Italy

   With C. Giannelli. Integrating neural networks and isogeometric analysis for forward and inverse problems governed by PDEs.

3. Sep 2026
   Research stay
   SISSA mathLab · Trieste, Italy

   With F. Pichi. Riemannian structure of the neural network manifold.

4. May 2026
   Research stay
   Institut Camille Jordan, Université Claude Bernard Lyon 1 · Villeurbanne, France

   With C. Marcati. Scalable natural gradient methods and tensor-train approaches for the Gross–Pitaevskii equation.

5. Sep 2025 — Nov 2025
   Research stay
   Politecnico di Torino, DISMA · Turin, Italy

   With S. Berrone and C. Canuto. Loss functions based on a posteriori error estimators for training neural networks that approximate PDE solutions.

6. Feb 2024 — Mar 2024
   “Master’s valorisation” internship
   EPFL, Chair of Numerical Modelling and Simulation · Lausanne, Switzerland

   With A. Buffa and Y. Voet. Model order reduction for time-dependent PDEs, with applications to isogeometric discretisations.

7. Jul 2023 — Sep 2023
   Research assistant
   EPFL, Department of Mathematics · Lausanne, Switzerland

   With F. Henríquez. Multi-fidelity neural network surrogates for large-scale Bayesian inverse problems, applied to inverse acoustic scattering by random domains.

Industry experience

1. Sep 2022 — Feb 2023
   Reinforcement learning intern — race strategy
   Alfa Romeo F1 Team ORLEN (Sauber Motorsport AG) · Hinwil, Switzerland
   • Developed the simulation environment for an AI agent for live race strategy.
   • Studied the convergence of reinforcement learning algorithms in a highly stochastic setting.
   • Implemented F1-specific versions of DQN, PPO and SAC.
   • Led the migration of the code base from TensorFlow to PyTorch.
2. 2018 — 2023
   Freelance consultant
   Roboris Srl · Pisa, Italy

   Consulting activities in robotics software.

Awards & fellowships

1. 2026
   SIAM Travel Award
   SIAM — to attend the SIAM Conference on Mathematics of Data Science (MDS26), Salt Lake City
   SIAM travel support
2. 2026
   Full fee waiver — Pathfinder Innovation Bootcamp
   Fondazione Miticoro
3. 2024
   Best Master Average Grade 2024
   EPFL — highest average grade across all Master’s programmes
4. 2024
   Prix Douchet 2024
   EPFL Mathematics Section — highest average grade in the Master’s
5. 2024 — 2027
   Marie Skłodowska-Curie Doctoral Fellowship
   IN-DEEP European Doctoral Network
6. 2019 — 2021
   Merit-based reduction of university fees
   Università di Pisa

Organisation of scientific events

1. Sep 2026
   Minisymposium “Preconditioning in and for Scientific Machine Learning”
   YAMC 2026, Turin — co-organiser
   Conference
2. Jun 2026
   Minisymposia MS02 “Advances in Neural Network Approximation and Surrogate Modeling for SciML” and MS04 “High-Order Numerical Methods for Complex Mechanics and Higher-Order PDEs”
   GIMC SIMAI Young 2026, Pisa — co-organiser
   ConferenceBook of abstracts
3. Sep 2025
   Minisymposium “Recent Advances in Scientific Machine Learning: From Theory to Applications”
   YAMC 2025, Padua — co-organiser
   Conference
4. May 2025
   Lombardy Young Numerical Analysts (LYNUM VI)
   Pavia — conference co-organiser
   Website
5. Mar 2025
   Advanced Scientific Programming in Python
   Pavia — seminar co-organiser
6. Feb 2025
   Joint GNCS-SIAM Chapters Meeting for Young Researchers in Numerical Analysis and Applied Mathematics
   Pavia — conference co-organiser
   Website
7. 2024 —
   PAV-IA: Beyond informal AI talks
   Pavia — seminar series co-organiser
   Website

Affiliations

1. 2026 —
   Member, Y-SIMAI (Young SIMAI) Committee
2. 2026 —
   Member, SIMAI — Società Italiana di Matematica Applicata e Industriale
3. 2025 —
   Member, INdAM-GNCS — Gruppo Nazionale per il Calcolo Scientifico
4. 2024 —
   Founder; President 2024–2025, Università di Pavia SIAM Student Chapter
5. 2024 —
   Member, UMI — Unione Matematica Italiana
6. 2022 —
   Member, SIAM — Society for Industrial and Applied Mathematics

Skills