Davide Lionetti is an audio-software engineer, musician, and PhD candidate at IPEM, Ghent University, specializing in the intersection of musicology and Human-Computer Interaction.
With a background in IT Engineering (B.Sc. at UniPD) and Music Engineering (M.Sc. at PoliMi), he has expertise in digital signal processing, deep learning, and creative programming for augmented musical instruments.
He is passionate about integrating immersive audio and computational creativity into XR applications. Skilled in programming languages like Python, PureData, and SuperCollider, Davide leverages his multidisciplinary musical knowledge to advance smart musical instruments and music interaction design.
Davide has developed two Digital Musical Instrument (DMI): the Handmonizer (presented at IS2-2023) and the Muscle Guided Guitar Pedalboard(featured at NIME 2024). The latest, explores the application of deep learning-based sEMG analysis to enhance audio effects.
His main interests spans these two fields:
- Human-computer Interaction applied to Music technology: applied in his project the Handmonizer. It presents a DMI designed for the jazz singer Maria Pia De Vito, an artistic-oriented voice harmonizer driven by her hand through an ANN. You can watch a short video demonstration in which the artist tried to merge the Handmonizer with her current setup or read the full scientific paper.
- Deep learning applied to music technologies: Explored during the Master thesis The Augmented Guitarist and other projects such as the 3Dreams: an immersive VR experience.
other interests:
- Plugin development merged with Machine learning and Deep learning, especially VST development linked with Music interaction design as I did in two of my projects the Handmonizer, an artist-oriented vocal harmonizer and the handy fm synthesizer.
- Creative programming merged with Deep learning for New media art development focused on the user interaction like the artistic VR experience 3Dreams based on a Music emotion recognition network to track the emotional contour of a song.
- Computer Music software development as the Synesthetic or the Flanger vst plugin implemented in Juce.
- Machine learning and deep learning for audio application, especially for audio synthesis, music information retrieval and algorithmic composition as I did in the bachelor's degree IT engineering thesis hosted by Antonio Rodà and entitled Elaboration of a Lead Sheet Dataset for Computational Creativity Systems.
- Playing guitar 🎸 sing 🎤 and produce music in Ableton 🎼. Check his song in Spotify
- Reading and poetry 📚.
- Doing sports such as martial arts and Chalistenics 🏃♂️.
You can find me on LindedIn, or download my Resume, write to me for any proposal or info.
