Physicist, currently a PhD candidate in the National PhD Program in AI & Society, funded by the Italian National Institute for Nuclear Physics (INFN). His research activity focuses on magnetic resonance imaging, particularly diffusion-weighted MRI and MR fingerprinting, with a solid background in radiological physics, medical imaging, and radiotherapy. He carries out research activities in collaboration with the University of Oxford, contributing to international projects in the field of advanced imaging and the application of Artificial Intelligence to medicine. His work focuses on the application of Deep Learning techniques to the reconstruction of quantitative MRI maps, with particular interest in the implementation of neural networks (FCN and CNN) on Field Programmable Gate Arrays (FPGAs), with the aim of improving speed and energy efficiency compared to traditional CPU- and GPU-based solutions.
His research activity is conducted at INFN and the University of Bologna. Alongside his research work, he is a tenured Mathematics and Physics teacher at upper secondary school level. Teaching represents a central component of his professional profile: he shows a strong interest in education at all levels, particularly at high school level, with a focus on scientific rigor, conceptual clarity, and the development of critical thinking. In parallel with his school teaching, he collaborates with international educational tour operators in the design and delivery of Artificial Intelligence workshops for high school students, held as part of study-abroad programs in England. These activities aim to introduce students to AI topics through hands-on, interdisciplinary, and innovation-oriented approaches.
