Research & Papers
Explainable AI for Clinical Decision Support Systems
Introduces an interpretable deep learning framework for clinical decision support that provides human-readable explanations, improving physician trust and adoption rates.
Hassan Tariq, Mariam Yusuf
Quantum-Resistant Cryptography: Migration Strategies for Enterprise Systems
A practical migration framework transitioning legacy RSA/ECC infrastructure to post-quantum cryptographic standards with zero-downtime cutover strategies.
Khalid Mansour, Reem Abdullah
Real-Time Anomaly Detection in IoT Streams Using Graph Neural Networks
Proposes a graph neural network architecture for detecting anomalies in IoT data streams with sub-second latency, validated on real-world smart city deployments.
Omar Al-Zahra, Layla Karim
A Systematic Review of AI-Driven Software Testing Methodologies
A comprehensive systematic review analyzing 150+ studies on AI applications in software testing, identifying key trends, challenges, and opportunities for future research.
Mohammed Khalil, Sara Nouri
Federated Learning for Privacy-Preserving Healthcare Analytics
Demonstrates a federated learning framework enabling collaborative model training across hospitals without sharing patient data, achieving 94% diagnostic accuracy.
Yusuf Ibrahim, Nora Saleh
Optimizing Distributed System Performance Through Adaptive Resource Orchestration
This paper presents a novel approach to dynamic resource allocation in cloud environments, demonstrating significant performance improvements through machine learning-driven orchestration strategies.
Ahmed Al-Rashid, Fatima Hassan