Enrico Migliorini

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.


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.


ESR4 in the MOSAICS news

MOSAICS comes to a close paving the way for continued quality of life improvements for cochlear implant recipients

The end of September 2023 also marked the official end of the MOSAICS project, funded by the European Commission as the Marie Skłodowska-Curie European Industrial Doctorate (EID). With the key aim of improving the quality of life of cochlear implant (CI) recipients, the results of the MOSAICS project are set to pave the way for their uptake into further research and development of product, diagnostic and care improvements for cochlear implant users.

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