I am a Postdoctoral Researcher in Computational Musicology at the Digital and Cognitive Musicology Lab (DCML).
My main research focus lies on probabilistic modeling of musical structures at the moment, combining approaches from machine learning, Bayesian statistics, computer linguistics, and music theory. Besides, I am studying and developing methods related to representation learning and probabilistic programming.
In my PhD thesis The Learnability of the Grammar of Jazz: Bayesian Inference of Hierarchical Structures in Harmony, supervised by Martin Rohrmeier (EPFL) and Timothy O’Donnell (McGill University), I simulated how abstract knowledge about musical structure is learnable without a teacher from listening and engaging with music.
In 2015, I earned a master’s degree in mathematics and computer science at the TU Dresden where I in particular worked on geometric structures of voice-leading spaces. My research interests further include topics from mathematical music theory, music cognition, and computational cognitive science. 
Aside from my academic activities, I enjoy playing the upright bass in Jazz improvisations.