Dr Johan Pauwels

Profile

Johan Pauwels is a Lecturer with the Centre for Digital Music at Queen Mary University of London. He received Master of Science degrees in Electrical/Electronics Engineering (KU Leuven ’06) and Artificial Intelligence (KU Leuven ’07). In 2016, he obtained a PhD from Ghent University on the topic of automatic harmony recognition from audio. He has further held research positions at IRCAM and Imperial College of London and has also taught at City, University of London and the University of West London.

Teaching

In 2023-2024, I am teaching

• ECS7013P Deep Learning for Audio and Music (MSc/PhD)
• ECS411U Signals and Information (1st year UG)

Research

Research Interests:

Johan’s aim is to make machines understand music to the level of a trained professional, such that new tools can be developed to assist musicians performing live or in the studio, listeners navigating large music collections and learners studying music. To that end, he uses a combination of machine learning, signal processing, data science and music theory. In recent years, he has been working on narrowing the gap between academic research and user-centric applications, web-based music services and the personalisation of spatial and immersive audio.

Publications

Supervision

Currently, I'm part of the supervisory team of the following PhD students:

• Yannis Vasilakis (primary supervisor)
• James Bolt (secondary supervisor)
• Carlos De La Vega Martin (secondary supervisor)
• Jeff Miller (secondary supervisor)
• Kasia Adamska (secondary supervisor)
• Harnick Khera (secondary supervisor)

Most of these are funded through the UKRI Doctoral School in AI and Music.

Moreover, in a typical year I am supervising 8-10 BSc/BEng and 8-10 MSc students for their final year projects.