Expertise:

sound and music making and production, machine learning, human-computer interaction

Language(s) spoken:

English, Spanish

Gabriel Vigliensoni is an electronic music artist, performer, and researcher whose work currently explores the creative affordances of the machine learning paradigm in the context of sound- and music-making. His practice merges formal musical training with extensive studies and experience in sound recording, music production, music information retrieval, human-computer interaction, and machine learning to explore and develop novel approaches to music composition and performance.

Vigliensoni views sound and music as shared experiences that are completed through audience interaction. Over his extensive career, he has experimented with techno and breakbeat, merged krautrock with electronica, explored vocal-driven songs outside traditional pop formats, and utilized procedural composition techniques to challenge the liveness and immediacy of digital music production.

Vigliensoni's creative work and research have been showcased internationally at venues and conferences such as CCA (QC), CMMAS (MX), IRCAM (FR), MUTEK (QC, CL), ICCC (CA, PO), IKLECTIK (UK), ISEA (CA), NMF (UK), NIME (US), ICMC (US), and ISMIR (US, FR, BR, CN, NL). He earned a PhD in Music Technology from McGill University and currently serves as an Assistant Professor in Creative Artificial Intelligence in the Department of Design and Computation Arts at Concordia University.

Visit this expert's Faculty Profile