Saeed A. Shurrab ✌🏻
Saeed A. Shurrab
(he/his/him)

PhD Candidate

New York University Abu Dhabi
Tandon School of Engineering - NYU
I am currently pursuing a Ph.D. in Biomedical Engineering at New York University Abu Dhabi and the Tandon School of Engineering at NYU, as a Global Ph.D. Fellow with the Clinical AI Lab. In 2022, I earned my Master of Science in Data Science and Artificial Intelligence, with distinction, from Jordan University of Science and Technology. My master's studies were fully funded through the prestigious German Academic Exchange Service (DAAD) award. Prior to that, in 2014, I completed my Bachelor of Science in Industrial and Systems Engineering at the Islamic University of Gaza. My passion for data analytics, coupled with a strong belief in the transformative power of data to drive robust decision-making and innovative solutions, has led me to pursue a career in data science focused on machine learning applications for healthcare data.
Research Focus ✌🏻
My current research focuses on developing foundation models for structured electronic health record (EHR) data, with a particular emphasis on advancing the retrieval of patients historical events for clinical prediction tasks via retrieval-augmented techniques. I am interested in creating value-aware and context-sensitive encodings that better capture the complexity of patient trajectories, enabling more accurate prediction, retrieval, and decision-support systems. Ultimately, my goal is to design machine learning methods that are both clinically meaningful and computationally robust, driving progress toward safer, more reliable, and patient-centered applications of artificial intelligence in healthcare.
Featured Publications
Multimodal Deep Learning for Stroke Prediction and Detection using Retinal Imaging and Clinical Data
Multimodal masked siamese network improves chest X-ray representation learning
Multimodal Machine Learning for Stroke Prognosis and Diagnosis: A Systematic Review
Self-Supervised Learning Methods and Applications in Medical Imaging Analysis: A Survey
Recent Publications
Saeed A. Shurrab, Aadim Nepal, Terrence J. Lee-St. John, Nicola G. Ghazi, Bartlomiej Piechowski-Jozwiak, Farah E. Shamout (2025). Multimodal Deep Learning for Stroke Prediction and Detection using Retinal Imaging and Clinical Data. In EMBC.
DOI
Shaza Elsharief, Saeed A. Shurrab, Baraa Al Jorf, Leopoldo Julian Lechuga Lopez, Krzysztof J. Geras, Farah E. Shamout (2025). MedMod: Multimodal Benchmark for Medical Prediction Tasks with Electronic Health Records and Chest X-Ray Scans. In CHIL.
DOI Code Dataset Dataset Source Document
Saeed A. Shurrab, Alejandro Guerra-Manzanares, Farah E. Shamout (2024). Multimodal masked siamese network improves chest X-ray representation learning. Nature Scientific Reports.
DOI Code Dataset Preprint
Saeed A. Shurrab
Equal contribution
, Alejandro Guerra-Manzanares
Equal contribution
, Amani Magid, Bartlomiej Piechowski-Jozwiak, S. Farokh Atashzar, Farah E. Shamout (2024). Multimodal Machine Learning for Stroke Prognosis and Diagnosis: A Systematic Review. IEEE JBHI.
DOI
Saeed A. Shurrab
Equal contribution
, Yazan Shannak
Equal contribution
, Rehab Duwairi (2022). Retina Disorders Classification via OCT Scan: A Comparative Study between Self-Supervised Learning and Transfer Learning. IAJIT.
DOI Code Dataset
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