Eugenio Donati has dark brown hair and a beard. He's wearing a black jumper.

Dr Eugenio Donati

Lecturer in Audio Engineering
School of Computing and Engineering
eugenio.donati@uwl.ac.uk

I am a Lecturer in Audio/Sound Engineering and I have a PhD in Audio Electronics and Bio-signal processing. My doctoral thesis focused on the development of a system for the conversion of voice into MIDI through the application of biosignal and Artificial Intelligence. I am a member of the Institution of Engineering and Technology (IET) and of the UK Acoustic Network (UKAN+).

  • Research and publications

    Journal Articles

    Eugenio Donati, Christos Chousidis, Henrique DeMelo Ribeiro, Nicola Russo. “Classification of Speaking and Singing Voices Using Bioimpedance Measurements and Deep Learning”. Journal of Voice, Journal of The Voice Foundation and the International Association of Phonosurgery, 2023

    Nicola Russo, Haochun Huang, Eugenio Donati, Thomas Bruun Madsen, Konstantin Nicolic. “An Interface Platform for Robotic Neuromorphic Systems”. MPDI, Chips Journal, 2023

    Arturo Esquivel Ramirez, Eugenio Donati and Christos Chousidis. "A siren identification system using deep learning.” Elsevier, international Scientific Journal of Engineering Applications of Artificial Intelligence, 2022

    Eugenio Donati, Christos Chousidis. "Electroglottography based real-time voice-to-MIDI controller." Elsevier Journal of Neuroscience and Informatics, 2022

  • Conferences

    “Electroglottography based voice-to-MIDI real-time converter with AI voice act classification”, 17th IEEE Medical Measurement & Application conference (June 2022)

    “Development of a real-time voice-to-MIDI converter based on electroglottography, InMusic2019”, University of West London (December 2019)

    “Electroglottography based voice-to-MIDI real-time converter with AI voice act classification”, 17th IEEE Medical Measurement & Application conference (June 2022)

  • Research degree supervision

    Principal Supervisor

    “Improving speaker dependant anomalous speech detection using deep learning” (Daniel Lewis Tweddle)

    Second/third supervisor

    “Use of Otoacoustic emissions as biometric based on machine learning algorithm and cochleagram” (Samuele Calabrese)

Courses taught on