I am currently a PhD student in Physics at the University of Catania, in the Nuclear and Particle Physics curriculum. I earned my Master’s Degree in Physics (110/110) in 2025 with a thesis on "Optimization of the light detection system of the ICARUS detector", and my Bachelor’s Degree in Physics (110/110 cum laude) from the same university.
My research experience spans experimental particle physics and applied machine learning. As an INFN Associate, I contributed to the ICARUS experiment in collaboration with Fermilab (USA), focusing on photomultiplier gain stability and light detection system implementation.
I also participated in the FNAL Summer Student Program (2022), studying misidentified protons in simulated neutrino interactions to enhance reconstruction algorithms.
Since 2025, I have been a research fellow at INAF – Astrophysical Observatory of Catania, developing machine learning methods for anomaly detection in time series within the ATS library project (in collaboration with Banca Intesa Sanpaolo).
I have teaching experience as a Junior Tutor in physics laboratories and electromagnetism lessons and outreach experience as Vice-President of EPS Young Minds Catania (2023–2024) and as a participant in INFN KIDS educational events.
I have presented my research at national and international conferences, including IPRD25 (Siena, 2025), MAYORANA (Modica, 2025), and the 16th Pisa Meeting on Advanced Detectors (Isola d’Elba, 2024).
My research project focuses on the selection and reconstruction of electron neutrino interactions in the ICARUS (Imaging Cosmic and Rare Underground Signal) detector, part of the Short Baseline Neutrino (SBN) program at Fermi National Accelerator Laboratory (FNAL). Leveraging the intrinsic high spatial and calorimetric resolution of the Liquid Argon Time Projection Chamber (LAr-TPC) imaging, the main goal is to develop and optimize advanced tools based on Machine Learning (ML).