Projects
Research and applied projects across AI and Computer Science
Ongoing
A Memory-Driven AI for Advanced Gigapixel Whole-Slide Image Interpretation and Cancer Heterogeneity in Precision Oncology
A 4-year collaborative project to develop TITAN, a memory-driven AI framework that enables hierarchical, multimodal analysis of gigapixel pathology images, genomic profiles, and clinical data to improve early cancer diagnosis and personalized treatment planning.
Completed
Developing Adaptive Federated Learning Frameworks for Heterogeneous and Dynamic Electronic Health Records
Selected for funding after competitive assessment. Designs adaptive federated learning architectures for privacy-preserving analysis of distributed electronic health records across institutions in the UK and Saudi Arabia.
Utilizing Deep Learning Techniques for the Automated Diagnosis of Retinopathy of Prematurity (ROP)
A retrospective study developing and validating AI models for diagnosing ROP from fundus images using deep learning. Leverages a large Saudi-based multi-center dataset of over 29,000 retinal images to provide scalable, cost-effective, and non-invasive screening tools.