Università della Svizzera italiana (USI) - Ph.D. Student
2020 — OngoingCurrently, I am a Ph.D. Student at the Swiss AI Lab IDSIA and USI Università della Svizzera Italiana, under the supervision of Prof. Cesare Alippi.
Resume
Education
University of Oxford - Research visit
Mar 2024 — Aug 20246-month research visit within the group of Prof. Michael Bronstein.
Politecnico di Milano - MSc
2017 — 2020Master’s degree with honors (110/110L), defending a thesis on machine learning. During the two years of studies, I mostly attended AI-oriented courses.
Universitat Politècnica de València - Exchange
Sep 2018 — Jan 2019During the semester spent abroad – in Valencia – within the Erasmus program, I attended Spanish and English courses on programming, robotics and AI.
Politecnico di Milano - BSc
2014 — 2017The course program covered general topics of engineering and computer science.
Liceo C. Caminiti (IT) - High School
2009 — 2014High school diploma with a specific focus in mathematics and science.
Teaching
Advanced Topics in Machine Learning (MSc)
Sep 2024 — Jan 2025 @ USIGuest lecturer, teaching assistant, and tutor for team projects.
Advanced Topics in Machine Learning (MSc)
Sep 2023 — Jan 2024 @ USITeaching assistant, involved in course organization, lecture preparation and student tutoring.
Graph Deep Learning (MSc)
Feb 2023 — Jun 2023 @ USILectures design and students tutoring on team projects.
Advanced Topics in Machine Learning (MSc)
Sep 2022 — Jan 2023 @ USIStudents tutoring for projects on reproducibility.
Graph Deep Learning (MSc)
Feb 2022 — Jun 2022 @ USII gave a lecture on Spatiotemporal Graph Neural Networks and tutored students on projects.
Introduzione all’Intelligenza Artificiale e ML (MSc)
Sep 2021 — Jan 2022 @ USICourse on AI and ML delivered in Italian for high school teachers.
Machine Learning (BSc)
Feb 2021 — Jun 2021 @ USILab sessions on practical aspects and show how to design machine learning solutions to real-world problems.
Industry Projects
GraPV
Sep 2020 — Feb 2023Developing of graph-based methods for multi-site photovoltaic power forecasting, to improve accuracy on portfolio production prediction. The solution is based on novel graph-based AI strategies exploiting existing heterogeneous information and related dependencies. Joint project in collaboration with DXT Commodities, funded by Innosuisse.