About Me

Hi! I'm Megan 👋

I am a PhD researcher at Durham University, investigating the application of multimodal machine learning to understand and explain music performance difficulty for music education applications. I am supervised by Dr Chris Willcocks, Dr Brian Bemman, and Dr Mark Gotham, and am a member of the Artificial Intelligence and Human Systems (AIHS) group within the Department of Computer Science.

Prior to this, I completed a Master's degree in Culture Technology at the Music and Audio Computing Lab (MACLab) at the Korea Advanced Institute of Science and Technology (KAIST), under the supervision of Prof. Juhan Nam, and a Bachelor's degree in Computer Science at the University of Cambridge.

Publications

• MetaMatch: Reconciling Metadata for Aggregating Music Difficulty Annotations
  Megan E. Finch, Chris G. Willcocks, and Mark R. H. Gotham (2026). Proceedings of the 27th International Society for Music Information Retrieval Conference (ISMIR), Abu Dhabi, UAE
  [BibTeX]
• PIAST: A Multimodal Piano Dataset with Audio, Symbolic and Text
  Hayeon Bang, Eunjin Choi, Megan Finch, Seungheon Doh, Seolhee Lee, Gyeong-Hoon Lee, and Juhan Nam (2024). Proceedings of the 3rd Workshop on NLP for Music and Audio (NLP4MusA), pages 5–10, Oakland, USA. Association for Computational Linguistics
  [PDF][BibTeX][Google Scholar]