I am a final-year Computer Engineering undergraduate at the German University in Cairo (GUC), and conducted my Bachelor's Thesis research at the University of Bonn in Germany.
My technical focus lies at the intersection of Data Engineering, Applied AI, and Software Quality Automation. I love building robust data pipelines, training uncertainty-aware deep learning models, and engineering automated testing frameworks that save hundreds of hours of manual work.
- 🎓 Researching: Currently working on "Uncertainty-Aware Deep Learning for Precision Agriculture" using PyTorch at the University of Bonn.
- 💼 Working: Spearheading automation testing at Si-Ware Systems (saving the team 15+ hours/week).
- 🛠 Building: Real-time data streaming architectures using Apache Kafka, Spark, and Docker.
- 🏆 Achieving: DAAD Scholar (2024) and Cambridge Top in World (A-Level CS).
- 📫 Reach me: [email protected]
Languages
Data Engineering & AI
Testing & Tools
An end-to-end data engineering pipeline for real-time market analysis.
- Tech: Python, Apache Kafka, Spark, Docker, PostgreSQL.
- Highlights: Orchestrated containerised microservices to ingest, clean (KNN imputation), and stream trade data. Performed real-time aggregation on liquidity and sector performance.
Research conducted at the University of Bonn.
- Tech: PyTorch, Computer Vision, Python.
- Highlights: Developed models to detect crop nutrient deficiencies utilising high-res imagery. Analysed trade-offs between predictive accuracy and uncertainty calibration to support risk-sensitive decision systems.
- DAAD Scholarship for Exceptional Students (2024): Awarded to top-ranked students based on GPA performance across all faculties.
- Outstanding Cambridge Learner Award: Achieved the highest global score in Cambridge International A Level Computer Science.
Let's connect and build something impactful!