Tom Collins

Lecturer (Assistant Professor) in Music Technology.

Tom graduated in Music from Robinson College, Cambridge (MA 2005), and then from a second undergraduate degree in Mathematics and Statistics from Keble College, Oxford (MA 2008). He undertook doctoral work at the Faculty of Mathematics, Computing and Technology, The Open University, Milton Keynes, UK from 2008 to 2011. The PhD, titled Improved methods for pattern discovery in music, with applications in automated stylistic composition, was supervised by Robin Laney, Alistair Willis, and Paul Garthwaite.

Profile

Tom has held several postdoctoral positions: at the Center for Mind and Brain, UC Davis, USA from 2011 to 2012; at the Department of Computational Perception, Johannes Kepler University Linz, Austria from 2013 to 2014; and as an early career research fellow in the Music, Technology and Innovation Research Centre, Faculty of Technology, De Montfort University, Leicester, UK from 2014 to 2016.

In 2015, he founded Music Artificial Intelligence Algorithms, Inc., with long-term collaborator Christian Coulon, with the aim of providing interfaces that transform the way users make, share, and understand music.

Alongside this project, he has held positions as Visiting Assistant Professor, in the Department of Psychology, Lehigh University, USA from 2016 to 2018, and then in the Department of Computer Science, Lafayette College, USA from 2018 to 2019.

 

Departmental Roles

  • Chair of Ethics Committee

 

Research

Tom's main research interests comprise:

  • Machine learning applied to music, including but not limited to automatic generation of stylistic compositions, incorporation in software, and the technology's effect on student education and work
  • The Web Audio API and resultant possibilities for musical creation, consumption, and collaboration
  • Discovery of repeated patterns in music, visual, and other domains
  • Voice recognition and natural language processing for music editing and analysis (e.g., given a query like 'perfect cadence followed by homophonic texture', retrieve the relevant events from a digital score)
  • Musical expectancy and listening choices (for symbolic/audio input and different listener backgrounds/contexts)

Find out more information about the Music Computing and Psychology Lab.

The publications arising from the lab's work cross boundaries between music, computing, psychology, mathematics, and statistics. As an example, a paper on cognition of tonality appeared in Psychological Review (Impact Factor 7.6, and 5th out of 128 journals in the category Psychology – Multidisciplinary).

Tom has contributed to the following funded research projects:

  • Wittgenstein Grant (Austrian Science Fund project no. Z159)
  • Modeling Tonal Structure in Music: From Theory to Behavior and Brain Function (National Science Foundation grant no. 1025310)

Contact details

Dr Tom Collins
Lecturer (Assistant Professor) in Music Technology
Department of Music
University of York

http://tomcollinsresearch.net/