Bachelor's in Data Science from the Faculty of Computers and Data Science, Alexandria University — CGPA: 3.62
I work mainly with Data Science, Machine Learning, and Applied AI topics, focused on building end-to-end systems that turn data into practical solutions.
My interests span machine learning, deep learning, computer vision, NLP, and data analytics.
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3rd Place in Egypt — HackAtom by ROSATOM 2026
Competed in the AI & Robotic Systems in Nuclear Energy track as part of Team Pantomath. -
ECPC — Egyptian Collegiate Programming Contest
Placed 84th out of 214 teams in my first ECPC participation.
An AI-powered drug-drug interaction prediction system designed to identify potential interactions between medications using biomedical graph data and deep learning.
The project combines heterogeneous biomedical information from sources including DrugBank, TWOSIDES, and STRING, experimenting with graph neural network architectures such as GAT and R-GCN alongside molecular and semantic drug representations.
My work focused mainly on data exploration and preparation, biomedical feature engineering, GNN experimentation, model evaluation, and technical analysis as part of the project's data and machine-learning team.
The final system integrates the prediction pipeline with a web platform, inference APIs, and an AI-assisted explanation layer.
Python PyTorch PyTorch Geometric Graph Neural Networks Neo4j BioBERT FastAPI .NET
A real-time computer vision system designed to monitor driver behavior and detect both drowsiness and distracted driving through a webcam feed.
DriveGuard combines YOLO-based behavior detection with eye-aspect-ratio temporal analysis to distinguish normal blinking from sustained drowsiness. It can identify distracted behaviors including phone use, smoking, and eating, while triggering visual and audio alerts when unsafe behavior is detected.
The distraction detection model achieved an 89% mAP50, and the system also supports optional event logging with timestamps, event duration, and alert status.
Python OpenCV YOLO PyTorch TensorFlow NumPy Pandas Flask
- Data Science & Data Analytics
- Machine Learning & Deep Learning
- Computer Vision
- Natural Language Processing
- AI-powered applications
- Data Visualization & Business Intelligence
I'm always interested in opportunities to learn, collaborate, and work on meaningful data and AI projects.