In April 2018, the Data Science for Music Challenge Initiative awarded four, one-year  grants of $75,000 each for research projects at the intersection of music and data science.

Submissions were solicited for potential areas of study listed below. Note that this list is not exhaustive:

  • Auditory presentation and analysis of data;
  • Algorithms and computer composition;
  • Computational analysis of music and music perception;
  • Performance analysis;
  • Big Data-based acoustics or instrument design;
  • The analysis of music education methods;
  • Designing music and sound for use in healthcare, advocacy and other settings;
  • “Crowd sourcing” for collaborative music making and experience;
  • Music recommender systems;
  • Data-based fundraising strategies for music organizations.

The funded projects are listed below. Please see the MIDAS press release for more information.

  • Understanding and Mining Patterns of Audience Engagement and Creative Collaboration in Large-Scale Crowdsourced Music Performances
    Investigators: Danai Koutra and Walter Lasecki, both assistant professors of computer science and engineering
  • Understanding How the Brain Processes Music Through the Bach Trio Sonatas
    Investigators: Daniel Forger, professor of mathematics and computational medicine and bioinformatics; James Kibbie, professor and chair of organ and university organist
  • The Sound of Text
    Investigators: Rada Mihalcea, professor of electrical engineering and computer science; Anıl Çamcı, assistant professor of performing arts technology
  • A Computational Study of Patterned Melodic Structures Across Musical Cultures
    Investigators: Somangshu Mukherji, assistant professor of music theory; Xuanlong Nguyen, associate professor of statistics