Elona Shatri

Elona Shatri is a PhD candidate at the UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM) and a visiting lecturer at Queen Mary University of London's School of Electronic Engineering and Computer Science. She specializes in Optical Music Recognition (OMR) using Deep Learning and is a leading advocate for ethical AI practices. Her research focuses on advancing OMR techniques, including GAN-based music synthesis and dataset development (e.g., DoReMi), while addressing challenges in low-data scenarios and historical manuscripts. She teaches postgraduate courses on Machine Learning and Visual Data Analysis, blending technical rigor with creative applications.

Research Interests: OMR with deep learning, ethics in AI, generative AI models, music informatics, and interdisciplinary collaborations between AI and the arts.

Awards: Recipient of the Best Student Paper Award at the 2024 Knowledge Discovery in OMR conference for her work on instance segmentation.

Projects: Co-lead on the UK-Qatar AI Collaboration (2024–) and the CREAATIF project examining AI in creative industries. Founded the QMUL AI and Ethics Research Group, fostering interdisciplinary dialogues on fairness, transparency, and societal impacts of AI.

Labs/Teams: Centre for Digital Music (C4DM), part of Queen Mary's School of Electronic Engineering and Computer Science.