Co-authors
4
list available
Resume (English only)
Academic Achievements
- Authored the foundational paper 'Understanding OMR'.
- Created and released the MUSCIMA++ dataset, widely used in OMR research.
- Recent work focuses on practical recognition of pianoform notation and domain adaptation techniques like data synthesis for manuscript recognition.
- Pioneering digital analysis of Gregorian Chant, exploring appropriate music theories for its eight modes and using bioinformatics methods to trace melodic development.
- Co-authored an ISMIR 2025 paper on a computational model of saxophone playing difficulty.
- Produced a technical report for the GAUK1444217 project.
Research Experience
- 2023–2027: Principal Investigator of the OmniOMR project (NAKI III programme, Ministry of Culture of the Czech Republic), focusing on optical music recognition for digital libraries.
- 2023–2029: Co-Investigator and leader of the Chant Analytics team in the SSHRC-funded 'Digital Analysis of Chant Transmission' project (Canada).
- 2023–2024: Principal Investigator of the 'Genome of Melody' project (funded by John Templeton Foundation via Cultural Evolution Society), applying phylogenetics to study Gregorian Chant melody evolution.
- 2017–2019: PI of the GAUK project 'Multimodal Optical Music Recognition' (GAUK 1444217).
- 2017–2018: Co-investigator of 'Convolutional Neural Networks for Optical Music Recognition' (GAUK 170217).
- 2015–2016: PI of 'rRNA Secondary Structure Prediction' (GAUK 550214), which led to the rPredictor database.