EEG-Based Alzheimer’s Disease Classification
A novel graph-based transformer framework achieving 99.1% accuracy for Alzheimer’s Disease classification — 7-18 percentage points above state-of-the-art
Portfolio
Arabic LLM Evaluation Framework
A comprehensive rubric-based evaluation framework for assessing Arabic Large Language Models in educational conversational applications
Medical Imaging AI at Contrast AI
State-of-the-art computer vision models for medical imaging applications with focus on generative models
Explainable AI for NLP Dataset Debugging
X-Deep: A Human-in-the-Loop framework using LIME and SHAP for systematic error analysis in NLP datasets - Published in Nature Scientific Reports