Mohamed Erfan

Ran 200+ controlled experiments on Quantum Machine Learning (QML) classifiers using Python and scikit-learn, benchmarking
accuracy and F1 scores across multiple algorithm configurations to identify top-performing models.
Managed the full experimental pipeline — data preprocessing, feature selection, cross-validation, and confusion matrix analysis —
ensuring results were reproducible and statistically sound.
Co-authored a research paper documenting methodology, findings, and limitations for departmental publication.