Curriculum Vitae 

• Apr. 2024 - Mar. 2027 (expected)

Università di Pavia (UniPV), Pavia, Italy
Ph.D. in Computational Mathematics, Learning, and Data Science

• • Research topic: Mathematically certified deep learning algorithms for inverse problems governed by PDEs. Application to the personalized treatment plans in oncology.

  • Fellowship: Marie Skłodowska-Curie Doctoral fellowship within the IN-DEEP European Doctoral Network.

  • Supervisors: Dr. Alessandro Reali, University of Pavia (UniPV,  Italy), Dr. Giancarlo Sangalli, University of Pavia (UniPV,  Italy), Dr. Claudio Canuto, Polytechnic Institute of Turin (POLITO, Italy).

• Sep. 2021 - Feb. 2024

École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
M.Sc. in Computational Science and Engineering

• • Grade-Point Average (GPA): 5.96/6.00.

  • M.Sc. Thesis: "Preconditioned Low-Rank Riemannian Optimization for Multiterm Linear Matrix Equations", under the supervision of Professor D. Kressner and Professor L. Robol.

• Sep. 2018 - Jul. 2021

Università di Pisa (UniPi), Pisa, Italy
B.Sc. in Mathematics (curriculum: Computational oriented to Computer Science)

• • Final Grade: 110/110 cum Laude

  • Grade-Point Average (GPA): 30.92/30 (where 30/30 cum laude is 31/30 ).

  • B.Sc. Thesis: "Low-rank numerical methods for the Sylvester equation (original title: Metodi numerici low-rank per l’equazione di Sylvester)", under the supervision of Professor D.A. Bini.

• 2013 - 2018

Liceo Scientifico "U.Dini", Pisa, Italy
Diploma di Liceo Scientifico

• • Final grade: 100/100 cum Laude

• Feb. 2024 - Mar. 2024

EPFL MNS, Chair of Numerical Modelling and Simulation, Lausanne, Switzerland

Invited “Master’s valorisation” internship

Role: Conducted research activities under the supervision of Prof. A. Buffa and Y. Voet. Working on Model Order Reduction for time-dependent PDEs, with applications to isogeometric discretizations.

• Jul. 2023 - Sep. 2023

École Polytechnique Fédérale de Lausanne (EPFL), Department of Mathematics, Lausanne, Switzerland

Research activity under the supervision of Dr. F. Henríquez

Role: Extended a prior Semester Project titled "Multi-Fidelity Surrogate Modeling for Large-Scale Bayesian Inverse Problems using Artificial Neural Networks", with a focus on its application to inverse acoustic scattering by random domains.

• Sept. 2022 - Sep. 2023

Alfa Romeo F1 Team Orlen (Sauber Motorsport AG), Hinwil, Switzerland

Internship: Reinforcement Learning for the race strategy application in Formula 1

Role: Responsible for enhancing an AI agent for Live Race Strategy in F1 Grand Prix:

• Developed the simulation environment.

• Studied the convergence of Reinforcement Learning (RL) algorithms in a highly stochastic setting.

• Implemented F1-specific versions of state-of-the-art RL algorithms such as DQN, PPO and SAC.

• Led the migration of the code from TensorFlow to PyTorch.

• Feb. 2018 - Dec. 2023

Roboris Srl, Pisa, Italy

Consulting activities (freelancer)

• Jun. 2016 - Jul. 2016

Roboris Srl, Pisa, Italy

Young Apprenticeship: Introduction to C++ programming

• EPFL – Best Master average grade 2024: Intended to reward the EPFL student who has obtained the best average in the Master’s studies, across all sections.  

• Prix Douchet 2024 - EPFL Mathematics Section: Intended to reward the student in the Mathematics who has obtained the best grade average during his or her Master’s studies.

Programming Languages

• Python (Advanced - Experience with Deep Learning libraries: PyTorch, Keras, TensorFlow)

• Julia (Advanced - Experience with Deep Learning and Linear Algebra libraries: Lux.jl, CUDA.jl, Krylov.jl)

• Matlab (Advanced)

• C, C++ (Intermediate)

Version Control

• Git

Scientific Writing and Presentations

• LATEX, Beamer

• Microsoft Word, Microsoft Powerpoint

• Italian - Native

• English - Proficent (C2 CEFR)