The post-doctoral project espacelatentmatérialisant combines artistic, scientific, and technical work. It intends to explore theoretical and practical concepts such as behaviour, attention, and intra-action around the themes of generative deep learning and ecological landscape. It aims to address aesthetic, epistemological, and ethical research questions through the creation of a landscape-generating device, based on the deep learning of sounds and images collected from a situated environment. It relies on a diffractive method to articulate the scientific collection of sounds and images, the prototyping of a deep learning tool, the creation of an artistic dispositif, and collective experimentations, through research-creation.

Biography

Hugo Scurto (1993, Marseille, Fr) is a researcher, musician and designer. Their research employs art, design, and science to craft, prototype, and diffract machine learning within an ecology of music. Their practice consists in creating, listening and performing with learning machines to reveal and reconfigure our musical entanglements with our environments. Hugo is currently a postdoctoral researcher at EUR ArTeC (Université Paris 8, EA 1573), a collaborator of the Reflective Interaction group at EnsadLab, and a co-founding member of w.lfg.ng, an AI music collective. Before this, they completed a PhD in Machine Learning and Music Interaction at IRCAM (2016-2019), and were a visiting researcher at Department of Computing, Goldsmiths University in London (2015-2016). They graduated in Physics from École Normale Supérieure Paris-Saclay (2011-2016), received the MSc in Engineering from Sorbonne University (2015), and trained in Popular Music at Cité de la Musique de Marseille (2005-2011). With the support of a plurality of people, Hugo has published and presented work in international conferences and academic journals such as NIME, ACM TOCHI, DIS, or SIGGRAPH, and contributed to public events in cultural institutions such as Ars Electronica, Friche la Belle de Mai, GMEM, or Lutherie Urbaine.

PROJECT TEAM