Sabrina Hassan Moon’s research rethinks how artificial intelligence works on the devices people use every day, from health monitors to smart sensors, with a goal of making them faster, more reliable, and more energy efficient. Moon, who is a doctoral student at USF’s Bellini College of Artificial Intelligence, Cybersecurity and Computing, was awarded a $12,000 Dissertation Completion Fellowship to support the final stage of her work. The one-semester award includes a stipend along with a tuition waiver for up to nine credit hours, payment of student fees and coverage of health insurance premiums, allowing her to focus fully on completing her dissertation. “The fellowship gives me the opportunity to step away from my research and teaching assistant responsibilities for a semester and focus fully on completing my dissertation,” Sabrina said. “That dedicated time and support will be extremely valuable during the final stage of my doctoral work.” Moon earned a bachelor’s degree in electrical and electronics engineering in Bangladesh before coming to USF in 2022. Her advisor, Dr. Dayane Reis, is an assistant professor in the Bellini College. Sabrina’s research examines how AI applications can run efficiently on small, low-power devices known as edge devices, which can include fitness tracking devices, doorbells, speakers, thermostats, traffic monitoring systems, delivery drones, wearable heart monitors, smartphones and other portable medical devices. These are systems that process information in real time while operating under strict energy limits and imperfect conditions, challenges that traditional computing approaches struggle to address. To address these challenges, Moon focuses on a method called computing-in-memory, which allows devices to process data directly where it is stored instead of moving it back and forth between memory and processors. This shift can reduce energy consumption and improve speed, making it well suited for devices that must run and respond in real time.