ESR4 – Fitting, machine learning and Cochlear Implants
Host: Cochlear Ltd.
MOSAICS Research
Adapting the fitting process of cochlear implants through the use of machine learning techniques, aiming to improve performance on recipients, reduce the work load on audiologists, and allow identification of performance barriers caused by suboptimal fitting.
Background
Enrico comes from Florence, Italy. He developed a keen interest in neuroprosthetics in his teens after a family member received a cochlear implant. Since then, he’s been driven by a desire to push boundaries in human-computer integration. His interdisciplinary interest in brain interfaces is what led him to join the MOSAICS project.
Enrico holds a Bachelor’s Degree in Computer Engineering from the University of Florence (2016), with a thesis on neural network resilience to MPEG compression, and a Master’s Degree from the Polytechnic University of Milan (2019), with a thesis on the usage of Virtual Reality for evaluation of retinal neuroprostheses.