Authors

Théo Jourdan is Postdoctoral fellow part of the ISIR (Institut des Systèmes Intelligent et de Robotique) lab at Sorbonne Université in Paris. With a PhD in Computer Science about privacy and transparency in machine learning, his research focuses on the study of machine learning technology situated in human musical practices. His research adopts a critical perspective on this technology, as a way to include socio-cultural aspects of musical expression.

Teresa Pelinski is a PhD student part of the Augmented Instruments Lab, at the Centre for Digital Music at Queen Mary University of London. Her PhD is supported by UKRI and Bela. Teresa’s research focuses on developing tools for prototyping with ML in the context of musical practice, and on doing so from a practice research lens. Currently, she is also an Enrichment Student at the Alan Turing Institute.

Hugo Scurto is a music artist, designer and researcher, born and based in Marseille. They completed a PhD at IRCAM, were post-doctorate at École des Arts Décoratifs, Paris, and co-founding member of w.lfg.ng, an AI music collective. Their practice consists in creating, listening and performing with learning machines, in cooperation with a plurality of bodies, to reveal and reshape our musical entanglements with our environments.