I’m a data-driven professional with hands-on experience in Data Science, Machine Learning, Deep Learning, IT auditing, and quality management. My work blends practical industry expertise with research in data science, ML pipelines, federated learning, and NLP.
I specialize in building and securing intelligent systems—covering data pipelines, model training, and deployment. I enjoy turning complex requirements into clean, reliable solutions and documenting them so teams can operate confidently.
Summer School, GeoTraining — Universität Osnabrück, Germany (Aug–Sep 2025)
Focus: Data Analysis and Machine Learning with R
MSc, Data Science — Jordan University of Science & Technology (2023–2025)
Thesis: Securing ML Pipelines (Data Poisoning & Model Inversion in Federated Learning)
BEng, Electrical (Computers & Control) — Sana’a University (2017–2021)
Providing data analytics related services including cleansing, preprocessing, model development and implementation, dashboards development, documentation.
Audited and improved ISO-aligned QMS processes; led on-site audits, issued reports, and tracked corrective actions across technical and non-technical teams.
Led tutorials/labs, enforced lab safety, and taught undergrad courses (Python, Electrical Circuits).
Conducted IT audits, managed web maintenance, and handled IT admin tasks (backups, device upkeep).
Detection & mitigation for data poisoning and model inversion in FL pipelines with trust scoring and privacy mechanisms.
NAS via adaptive random search to optimize architectures efficiently.
Improves Arabic reading comprehension with entity-aware prompting strategies.
Transformer-based joint model for task-oriented dialogue.
Predicts numerical ratings from text reviews using classical ML + NLP features.
🚀 I’m open to roles and collaborations in Data Science, Analytics, & AI—let’s connect !!!