I am a Research Fellow in Cultural Analytics at University of Amsterdam (UvA). Working with large symbolic datasets of musical scores and harmonic annotations, I am primarily interested in Computational Music Analysis, Music Theory, Music Cognition, and their mutual relationship. My research is inherently interdisciplinary and aims to bridge the humanities and the sciences by drawing on methods and concepts from the Musicology and Music Theory, Mathematics, Music Information Retrieval, Data Science and Machine Learning, Music Psychology and Cognition, and the Digital Humanities.
Before my appointment at UvA, I worked as a postdoctoral researcher in the Digital and Cognitive Musicology Lab (DCML) at École Polytechnique Fédérale de Lausanne (EPFL, Switzerland) for the project Distant Listening: The Development of Harmony over Three Centuries (1700–2000), funded by the Swiss National Science Foundation (PI: Martin Rohrmeier). I also directed the project Digitizing the Dualism Debate: A Case Study in the Computational Analysis of Historical Music Sources, supported by the EPFL-UNIL funding scheme CROSS - Collaborative Research on Science and Society.
PhD in Digital Humanities, 2019
École Polytechnique Fédérale de Lausanne, Lausanne Switzerland
Staatsexamen Lehramt für Gymnasien und Gesamtschulen (Mathematik, Musik, Erziehungswissenschaft), 2016
Universität zu Köln, Germany
MA in Musicology, 2012
Hochschule für Musik und Tanz, Köln, Germany
We introduce wavescapes, a novel visualization method for tonal hierarchies that combines the visual representation of keyscapes with music analysis based on the discrete Fourier transformation (DFT) and illustrate it by analyzing compositions by Josquin, Bach, Liszt, Chopin, Scriabin, Webern, Coltrane, and Ligeti.
Journal Articles, Conference Papers, Datasets