Staff profile

Nick Collins' research interests include live computer music, musical artificial intelligence, and computational musicology, and he is a frequent international performer as composer-programmer-pianist, from algoraves to electronic chamber music. He co-edited the Cambridge Companion to Electronic Music (Cambridge University Press 2007/2nd Edition 2017) and The SuperCollider Book (MIT Press, 2011/2nd Edition 2024), wrote the Introduction to Computer Music (Wiley 2009) and co-wrote Electronic Music (Cambridge University Press Introductions series, 2013). Sometimes, he writes in the third person about himself, but is trying to give it up.

Chapter in book

• Jack Code's Rebellion
  
  Collins, N. (2022). Jack Code’s Rebellion. In A. Blackwell, E. Cocker, G. Cox, A. McLean, & T. Magnusson (Eds.), Live Coding: A User’s Manual (pp. 64-65). Massachusetts Institute of Technology Press.
• The Future of Rhythm
  
  Collins, N. (2020). The Future of Rhythm. In R. Hartenberger & R. McClelland (Eds.), The Cambridge Companion to Rhythm. Cambridge University Press.

Conference Paper

• Unstable Audio: Code Bending Text-to-Music Generation
  
  Collins, N. (in press). Unstable Audio: Code Bending Text-to-Music Generation. In Proceedings of the AES International Conference on Machine Learning and Artificial Intelligence for Audio.
• Composing for AI Voice Model Choir
  
  Collins, N. (in press). Composing for AI Voice Model Choir. Presented at International Computer Music Conference, Boston.
• Remixing AIs: mind swaps, hybrainity, and splicing musical models
  
  Collins, N., Ruzicka, V., & Grierson, M. (2020). Remixing AIs: mind swaps, hybrainity, and splicing musical models. Presented at 1st Joint Conference on AI Music Creativity, Stockholm.
• A Javascript Musical Machine Listening Library
  
  Collins, N., & Knotts, S. (2019). A Javascript Musical Machine Listening Library. In Proceedings of the 2019 International Computer Music Conference (pp. 383-387). The International Computer Music Association.
• Sonification of the Riemann Zeta Function
  
  Collins, N. (2019). Sonification of the Riemann Zeta Function. In P. Vickers, M. Grohn, & T. Stockman (Eds.), Proceedings of the 25th International Conference on Auditory Display (ICAD 2019). (pp. 36-41). Georgia Institute of Technology. https://doi.org/10.21785/icad2019.003
• Computational analysis of musical influence: A musicological case study using MIR tools
  
  Collins, N. (2010). Computational analysis of musical influence: A musicological case study using MIR tools (J. Stephen Downie & R. C. Veltkamp, Eds.). International Society for Music Information Retrieval.

Journal Article

• Recording artist career comparison through audio content analysis
  
  Collins, N. (2025). Recording artist career comparison through audio content analysis. Royal Society Open Science, 12(7), Article 241647. https://doi.org/10.1098/rsos.241647
• Composition in the Age of AI
  
  Collins, N. (2020). Composition in the Age of AI. Ideas Sónicas. Advance online publication.
• “…there is no reason why it should ever stop”: Large-scale Algorithmic Composition
  
  Collins, N. (2018). “…there is no reason why it should ever stop”: Large-scale Algorithmic Composition. Journal of Creative Music Systems, 3(1).
• A new curated corpus of historical electronic music: Collation, data and research findings
  
  Collins, N., Manning, P., & Tarsitani, S. (2018). A new curated corpus of historical electronic music: Collation, data and research findings. Transactions of the International Society for Music Information Retrieval, 1(1), 34-55. https://doi.org/10.5334/tismir.5
• Corposing a History of Electronic Music
  
  Collins, N. (2017). Corposing a History of Electronic Music. Leonardo Music Journal, 27, 47-48. https://doi.org/10.1162/lmj_a_01010
• Towards Machine Musicians Who Have Listened to More Music Than Us: Audio Database-led Algorithmic Criticism for Automatic Composition and Live Concert Systems
  
  Collins, N. (2016). Towards Machine Musicians Who Have Listened to More Music Than Us: Audio Database-led Algorithmic Criticism for Automatic Composition and Live Concert Systems. Computers in Entertainment CIE., 14(3), Article 2. https://doi.org/10.1145/2967510
• A funny thing happened on the way to the formula: Algorithmic composition for musical theatre
  
  Collins, N. (2016). A funny thing happened on the way to the formula: Algorithmic composition for musical theatre. Computer Music Journal, 40(3), 41-57. https://doi.org/10.1162/comj_a_00373
• Live Coding and Teaching SuperCollider
  
  Collins, N. (2016). Live Coding and Teaching SuperCollider. Journal of Music, Technology and Education, 9(1), 5-16. https://doi.org/10.1386/jmte.9.1.5_1
• The Ubuweb Electronic Music Corpus: An MIR investigation of a historical database
  
  Collins, N. (2015). The Ubuweb Electronic Music Corpus: An MIR investigation of a historical database. Organised Sound, 20(1), 122-134. https://doi.org/10.1017/s1355771814000533
• Automatic Composition of Electroacoustic Art Music Utilizing Machine Listening
  
  Collins, N. (2012). Automatic Composition of Electroacoustic Art Music Utilizing Machine Listening. Computer Music Journal, 36(3), 8-23. https://doi.org/10.1162/comj_a_00135
• Live Coding of Consequence
  
  Collins, N. (2011). Live Coding of Consequence. Leonardo, 44(3), 207-211. https://doi.org/10.1162/leon_a_00164
• The Analysis of Generative Music Programs
  
  Collins, N. (2008). The Analysis of Generative Music Programs. Organised Sound: An International Journal of Music and Technology, 13(3), 237-248. https://doi.org/10.1017/s1355771808000332

Other (Digital/Visual Media)

• SuperCollider Music Information Retrieval Library
  
  Collins, N. (2013). SuperCollider Music Information Retrieval Library.

Report

• The Rarity of Musical Audio Signals Within the Space of Possible Audio Generation
  
  Collins, N. (2024). The Rarity of Musical Audio Signals Within the Space of Possible Audio Generation. None.
• OK Computer Analysis: An Audio Corpus Study of Radiohead
  
  Collins, N. (2022). OK Computer Analysis: An Audio Corpus Study of Radiohead. https://doi.org/10.48550/arxiv.2211.15834