Physics Master's degree graduate, currently attending the Italian National PhD in AI & Society, with a study grant founded by the INFN. My main field of research is Magnetic Resonance Imaging, in particular Diffusion-weighted MRI and MR fingerprinting. In general, I have a solid foundation in radiological physics, medical imaging and radiation therapy.
My current research focuses on applying Artificial Intelligence, specifically Deep Learning techniques, in Magnetic Resonance Imaging (MRI) for reconstructing quantitative health-related maps. The project involves redesigning two Neural Networks (FCNN and CNN) using Field Programmable Gate Arrays (FPGAs) to accelerate processing. The team aims to compare FPGA performance with CPUs and GPUs, emphasizing speed and energy efficiency. The research, conducted at the Italian National Institute for Nuclear Physics and the University of Bologna, combines expertise in medical AI and electronic skills developed for high-energy physics experiments. The goal is to enhance the efficiency of MRI data processing, making AI applications more feasible in clinical settings and potentially enabling mobile device use for telemedicine.
