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QMUL, School of Electronic Engineering and Computer Science

Centre for Digital Music Seminar Series

Seminar by:
Professor Thor Magnusson

Date/time: Monday 30th of May, 12:00-13:00

Location: Engineering Building G2, Mile End Campus & Online

Open to students, staff, alumni, public; all welcome. Admission is FREE, no pre-booking required.

Title: Music Technologies that learn. But what are they learning?

Bio: Thor Magnusson is a Professor in Future Music at the University of Sussex and a Research Professor at the Iceland University of the Arts. His work focuses on the impact digital technologies have on musical creativity and practice, explored through software development, composition and performance. He is the co-founder of ixi audio, and has developed audio software, systems of generative music composition, written computer music tutorials and created two musical live coding environments. He has taught workshops in creative music coding and sound installations, and given presentations, performances and visiting lectures at diverse art institutions, conservatories, and universities internationally.

In 2019, Bloomsbury Academic published Magnusson’s monograph Sonic Writing: The Technologies of Material, Symbolic and Signal Inscriptions. The book explores how contemporary music technologies trace their ancestry to previous forms of instruments and media, including symbolic musical notation. The book underpins current research, where, as part of the MIMIC project, where Magnusson has worked on a system that enables users to design their own live coding languages for machine learning Magnusson is currently running an ERC Consolidator project called “Intelligent Instruments” where the research is on our human perception of intelligent musical instruments, embedded with machine learning and other AI (see

Further information here:

Abstract: Music technologies are inscribed with music theory, whether those are musical instruments, symbolic systems, or signal manipulations of sound. These are all technologies for thinking about music, they are instruments of theory, implementing our classifications, abstractions and visions of music. Machine learning has entered the field of music with full force. But what are the modes of inscriptions when our technologies learn? What are they really learning? This talk will explore some issues relating to the design of intelligent instruments, from the perspective of the recently established Intelligent Instruments Lab.

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