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
- Knowledge Discovery in Optical Music Recognition: Enhancing Information Retrieval with Instance Segmentation, in Proceedings of the 16th International Conference on Knowledge Discovery and Information Retrieval, Best Student Paper Award, 2024.
- Synthesising Handwritten Music with GANs: A Comprehensive Evaluation of CycleWGAN, ProGAN, and DCGAN, IEEE Big Data 2024 2nd Workshop on AI Music Generation (AIMG 2024)), 2024.
- Low-Data Classification of Historical Music Manuscripts: A Few-Shot Learning Approach, The Sixth IEEE International Conference on Image Processing Applications and Systems, 2024
- Crafting Handwritten Notations: Towards Sheet Music Generation, in 6th International Workshop on Reading Music Systems, 2024
- DoReMi: First glance at a universal OMR dataset, in 3rd International Workshop on Reading Music Systems, 2021
- CompldNet: Sheet Music Composer Identification using Deep Neural Network, in 4th International Workshop on Reading Music Systems, 2022
- Towards Artificially Generated Handwritten Sheet Music Datasets, in 5th International Workshop on Reading Music Systems, 2023
- Improving Sheet Music Recognition using Data Augmentation and Image Enhancement, in 5th International Workshop on Reading Music Systems, 2023
- Optical Music Recogntion: State of the Art and Major Challenges, in The International Conference on Technologies for Music Notation and Representation, 2020
- Foundation Models for Music: A Survey
Proceedings Editor
- Proceedings of the 4th International Workshop on Reading Music Systems
- Proceedings of the 5th International Workshop on Reading Music Systems
- Proceedings of the 6th International Workshop on Reading Music Systems
Presentations
- E. Shatri, “Crafting responsive assessments of AI and tech futures (CREAATIF),” Poster presented at the Policy Forum of the Harvard Data Science Review’s Special Issue on Generative AI (GenAI), June 2024.
- E. Shatri, “Navigating the intersection of AI and creativity: A case study of musicians in the age of GenAI,” Presentation at the AI & Music Lecture Symposium and Jam, Bloomsbury Festival, October 2024.
- Enhancing Handwritten Music Sheet Datasets Using Generative Adversarial Networks, the 6th International Workshop on Reading Music Systems