Short CV/Education and training

  • 1996
    Masters in Musicology, Humboldt University Berlin, Germany.

  • 1998
    Masters in Mathematics, Humboldt University Berlin, Germany.

  • 2002
    PhD in Computational Musicology, Humboldt University Berlin, Germany, Supervisors: Prof. Dr. W. Auhagen (Musicology), Prof. Dr. Bernd Mahr (Computer Science).

  • 1998 – 2003
    PhD student and research assistant in the Interdisciplinary Research Group for Mathematical Music Theory KIT-MaMuTh, Technical University Berlin, Germany.

  • 2003 – 2005
    Postdoctoral Fellow, Music Computation and Cognition Laboratory, Viterbi School of Engineering, University of Southern California, Los Angeles, USA.

  • 2006 – 2010
    Postdoctoral Researcher, NWO-CATCH-project WITCHCRAFT, Department of Information and Computing Sciences, Utrecht University and Meertens Institute, Amsterdam, the Netherlands.

  • Since 2011
    Assistant Professor and project leader of NWO VIDI-project MUSIVA, Utrecht University, the Netherlands.

  • Since 2020
    Associate Professor, Department of Information and Computing Sciences, Utrecht University, the Netherlands.

Selected publications

  • Janssen, B., van Kranenburg, P., Volk, A. (2017). Finding occurrences of melodic segments in folk songs employing symbolic similarity measures, Journal of New Music Research, 46(2), 118-134.

  • Boot, P., Volk, A., & de Haas, W.B. (2016). Evaluating the Role of Repeated Patterns in Folk Song Classification and Compression, Journal of New Music Research, 45(3), 223-238.

  • Van Kranenburg, P., Volk, A., & Wiering, F. (2013). A Comparison between Global and Local Features for Computational Classification of Folk Song Melodies, Journal of New Music Research, Vol. 42 (1), 1-18.

  • A. Volk and A. Honingh (2012). Mathematical and computational approaches to music: challenges in an interdisciplinary enterprise. Journal of Mathematics and Music, Vol. 6 (2), pp. 73-81.

  • A. Volk and A. Honingh (Eds). Mathematical and Computational Approaches to Music: Three Methodological Reflection. Special Issue of the Journal of Mathematics and Music, Vol. 6 (2), 2012.

  • A. Volk and P. van Kranenburg (2012). Melodic similarity among folk songs: An annotation study on similarity-based categorization in music. Musicae Scientiae, Online publication doi:10.1177/1029864912448329

  • P. van Kranenburg, J. Garbers, A. Volk, F. Wiering, L.P. Grijp, R.C. Veltkamp (2010). Collaboration Perspectives for Folk Song Research and Music Information Retrieval: The indispensable Role of Computational Musicology. Journal of Interdisciplinary Music Studies, Volume 4 (1), art. #10040102, pp. 17-43.

  • F. Wiering, J. de Nooijer, A. Volk, H. J.M. Tabachneck-Schijf (2009). Cognition-based Segmentation for Music Information Retrieval Systems. Journal of New Music Research 38(2), pp. 139-154.

  • A. Honingh and A. Volk (2009), Mathematische muziektheorie: Nieuwe mogelijkheden voor muziekgerelateerd onderzoek. Dutch Journal of Music Theory, 14(3), pp. 181-193.

  • A. Volk (2008), The Study of Syncopation using Inner Metric Analysis: Linking Theoretical and Experimental Analysis of Metre in Music, In: Journal of New Music Research, Vol. 37 (4), pp. 259-273.

  • A. Volk (2008), Persistence and Change: Local and Global Components of Metre Induction using Inner Metric Analysis, In: Journal of Mathematics and Music, Vol. 2:2, pp. 99-115.

  • A. Volk and E. Chew (2008), Reconsidering the Affinity between Metric and Tonal Structures in Brahms' Capriccio Op. 76, No. 8, In: Computing in Musicology, Vol. 15.

Complete list of publications

Selected projects

  • NWO-VIDI-project MUSIVA (Modelling musical similarity over time through the variation principle), 2011-2016: The aim of this project is to deliver a cognition-based computational model on music similarity that grounds in the variation principle employed in classical, folk and popular music. The project will integrate knowledge and methods from Music Information Retrieval, Musicology and Cognitive Science. The assessment of similarity is fundamental for cognitive processes. However, no comprehensive theory exists on how listeners use similarity to predict, categorize or appreciate music. This is a major problem in the rapidly growing discipline of Music Information Retrieval (MIR). MIR researches methods that allow users to retrieve music that is similar to musical queries representing their needs via the Internet.This project investigates the fundamental principle of variation in music studied in Musicology and Cognitive Science as a means to establish similarity. Specifically, we take into account the interaction between global and local features of the music and will address music as unfolding in time. The project will deliver a model of music similarity that covers three major styles, namely classical, folk and popular music. The envisioned model will be based on cognitive and structural aspects of music, addressing high-level processes in establishing similarity. Hence, the project will make a major step towards cognition-based similarity models in music, which are urgently needed for the design of meaningful music retrieval systems. The development of a theoretic framework for similarity in music will contribute to the search for general principles of similarity across different domains envisioned in Cognitive Science.

Membership in scientific bodies/juries

  • Board member of the Society for Mathematics and Computation in Music (since 2007)

  • Editor-in-Chief of the Transactions of the International Society for Music Information Retrieval (since 2017)

  • Member of Computational Science Advisory Board of the Lorentz Center, International Center for Workshops in the Sciences, Leiden

  • Co-Founder and member of the international Women in MIR (WiMIR) Mentoring Programm

  • Co-Editor-in-Chief of the Transactions of the International Society for Music Information Retrieval (TISMIR)

  • Associate Editor of Musicae Scientiae

  • Editorial board member of Journal of New Music Research

  • Consulting Editor of Computing in Musicology

Media coverage

  • Concertzender live at Utrecht Centraal: Live interview at radio station Concertzender on 5 June 2017 about my public lecture "Lekker (algo)ritme" during the Culturele Zondag Utrecht Centraal.

  • Professoren op het podium (Professors on stage): A theater evening over Music and Mathematics, organized and moderated by Jan van den Berg. Guests: Anja Volk, Jan Neerven and Frank Redig. Theater de Veste, Delft. 1 April 2015, 20:30.

  • KennisCafe Amsterdam: Rocking Science, with Anja Volk, Tom ter Bogt, Fleur Bouwer, Louis Grijp, organized by De Volkskrant, KNAW, science center NEMO, de Balie Amsterdam, 15 December 2014, 20:00-22:00. Watch at De Balie TV, listen at Kennis van Nu, Radio 5.

  • Radio Interview at Science 071 Sleutelstad, 17 December 2014, listen here, photo here.

  • Interview "De Volkskrant", 10 December 2014

  • Presentation at Bessensap 2014 (Science meets press): "Hoe herken je muziek?", 6 June 2014,

  • Portrayal in De Groene Amsterdammer, 31st October 2013,

  • Computational musicology in De Groene Amsterdammer, October 2013

  • e-data & research nr. 4 March 2011

Additional qualifications

  • Bridging science and humanities research


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