Elona Shatri

AI Researcher | Ethics Advocate | Music Technologist

Elona Shatri

Welcome

Welcome to my portfolio! I explore the intersections of Artificial Intelligence, ethics, and music technology. Here, you’ll find my research, projects, and datasets.

About

I'm a PhD candidate at the UKRI Centre for Doctoral Training in Artificial Intelligence and Music (AIM). I am part of the Centre for Digital Music (C4DM) research group at Queen Mary University of London. My research interests include Optical Music Recognition as well as other MIR-related subfields. My goal is to have computers read sheet music computationally. I started working on this problem in September 2019 when I was granted the studentship from QMUL and Steinberg GmBH, with whom we collaborate closely. I am also the founder and a steering committee member of the QMUL AI and Ethics Research Group. This group critically examines the ethical dimensions of AI, with a focus on ensuring responsible and inclusive AI applications. The group organizes interdisciplinary seminars, collaborative workshops, and research projects that explore topics such as fairness, accountability, transparency, and the societal implications of AI technologies.

Research Interests

Optical Music Recognition: Enhancing information retrieval in OMR systems through new methodologies.

Ethics in AI: Exploring ethical considerations in AI, focusing on accountability, fairness, and transparency in applications across various domains.

Published Research

Proceedings Editor

Presentations

Projects and Datasets

Research Assistant (October 2024-): UK and Qatar joint Artificial Intelligence (AI) research commission

The UK and Qatar joint Artificial Intelligence (AI) research commission seeks to establish a roadmap for UK-Qatar collaboration on AI that will benefit both countries.

Research Assistant (February 2024-): Crafting Responsive Assessments of AI & Tech-Impacted Futures (CREAATIF)

Crafting Responsive Assessments of AI & Tech-Impacted Futures (CREAATIF) aims to bring the voices of creative workers into the foreground, particularly within policy guidance for the UK labour context.

DoReMi - Data Collection Lifecycle

The DoReMi dataset documents the lifecycle of Optical Music Recognition (OMR) data. It serves as a resource for advancing research in OMR systems.

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Blogposts and News

The 6th International Workshop on Reading Music Systems 2024

The 6th International Workshop on Reading Music Systems (WoRMS) took place virtually, bringing together researchers and practitioners from across the globe to discuss the latest developments in Optical Music Recognition (OMR). This year’s workshop featured three paper sessions, panels, and an insightful keynote by David Rizo, providing a comprehensive exploration of the state of OMR research and its real-world applications.

The 5th International Workshop on Reading Music Systems 2023

The 5th International Workshop on Reading Music Systems (WoRMS) took place on November 4th, 2023, in Milan, Italy, offering both on-site and remote participation. This year’s workshop showcased a range of cutting-edge research in Optical Music Recognition (OMR), including advancements in medieval music manuscripts, handwritten music synthesis, and few-shot learning.

The 4th International Workshop on Reading Music Systems 2022

The fourth edition of the International Workshop on Reading Music Systems (WoRMS) was held last Friday, offering another dynamic hybrid experience. Researchers and industry professionals in Optical Music Recognition (OMR) came together to explore the latest advancements and challenges in the field.

Optical Music Recognition: State of the Art and Major Challenges

Recently, I published my very first paper summarizing the state of the art and open challenges in Optical Music Recognition (OMR). The paper discusses paradigm shifts, evolving methodologies, and potential future directions for the field.

A Review on Generative Adversarial Networks

An exploration of how GANs have revolutionized machine learning by bridging generative and discriminative networks. The blog discusses their history, key advancements, and their implications in fields ranging from art to computer vision.

Contact

Feel free to reach out via email or connect with me on LinkedIn for collaborations and inquiries.