Timeline

  • Research Scientist
    Research Scientist in the Music Intelligence (MIQ) team, focusing on deep learning approaches for audio and music processing tasks.
    Spotify
    Berlin, Germany
  • Postdoctoral Researcher
    Causal deep learning research with applications to medical data
    German Centre for Neurodegenerative Diseases
    Bonn, Germany
  • Research Intern
    Music-to-lyrics alignment using end-to-end deep learning
    Spotify
    London, UK
  • Ph.D. in Machine Learning for Music Information Retrieval
    PhD at the Centre for Digital Music (C4DM). Dissertation: "Deep Learning for Music Information Retrieval in Limited Data Scenarios"
    Queen Mary University of London
    London, UK
  • M.Sc. in Computer Science
    Master's degree with a focus on music informatics. Thesis: "Constrained-Based Rearrangement of Music"
    Technical University Dortmund
    Dortmund, Germany
  • B.Sc. in Computer Science
    Bachelor's degree with a focus on computer vision, music informatics
    Technical University Dortmund
    Dortmund, Germany

Scholarly Activities

  • Meta-reviewer for the ISMIR conference (2025)
  • Tutorial: Lyrics and Singing Voice in MIR (ISMIR 2024)
  • Reviewer for the ISMIR conference (2015, 2018-2025) - Best Reviewer Award 2020
  • Reviewer for IEEE Transactions on Audio, Speech and Language Processing (8 reviews)
  • Reviewer for Neurocomputing and PeerJ Computer Science Journal

Research Supervision

PhD Students

  • Ningzhi Wang (Current) - Music representation learning

Research Internships

  • Morgan Buisson (2025) - Connecting user engagement to music preview locations
  • Joshua P. Gardner (2024) - Multi-modal music-text models for question answering (paper)
  • Emir Demirel (2023) - Novel deep learning architectures for lyrics processing tasks
  • Yu Wang (2022) - Few-shot musical source separation (paper)