Pharos University in Alexandria
Alexandria, Alexandria Governorate, Egypt
Bachelor
Computer Science
Grade: 3.27
Professional Summary
Education
Skills
Programming Languages
Python, C++, Java, Dart.
Software Development
Flutter, Git, Full-Stack Development.
Databases
SQL.
Core Skills
Algorithms, Data Structures, Problem Solving, Image Processing.
AI & Machine Learning
Machine Learning, Deep Learning, Computer Vision, PyTorch, TensorFlow, OpenCV, YOLO, Object Detection, Multi-Object Tracking, nlp.
Projects
Offside – AI Football Analytics System
Summary
Developed an end-to-end AI football analytics platform capable of extracting tactical and performance insights from a single broadcast football video as a graduation project.
Highlights
Developed robust player, ball, and referee detection using YOLO, achieving high accuracy in diverse football scenarios.
Implemented advanced multi-object tracking algorithms (ByteTrack and BotSORT) to ensure seamless tracking of dynamic elements throughout video frames.
Built and integrated jersey number recognition and team classification modules for granular player identification and comprehensive team analysis.
Engineered homography-based 2D pitch projection and semantic camera motion compensation, enabling precise spatial analysis and tactical visualizations.
Integrated football action recognition using an R3D-18 3D CNN, providing automated event detection and deeper tactical insights.
Generated comprehensive player statistics, including speed estimation, distance covered, possession analysis, and heatmaps, to inform performance evaluation.
Developed a scalable FastAPI backend with Supabase integration, ensuring efficient data processing, storage, and API access.
Built an intuitive Flutter mobile application for real-time analytics visualization, delivering interactive insights directly to users.
Real-Time Facial Emotion Recognition
Summary
Developed a real-time facial emotion recognition system using a custom Convolutional Neural Network (CNN).
Highlights
Designed and trained a custom CNN model, achieving accurate classification of five distinct facial emotions (Angry, Happy, Neutral, Sad, Surprised).
Built a real-time webcam inference system utilizing OpenCV for live emotion detection and immediate feedback.
Applied advanced image preprocessing and model optimization techniques, significantly improving system performance and inference accuracy.
Awards
Certificate of Recognition – ICMISI 2026 Smart Innovation Exhibition
IEEE
Presented Offside: An AI-Powered Sports Analytics & Management Platform at the Smart Innovation Exhibition during the IEEE International Conference on Machine Intelligence and Smart Innovation (ICMISI 2026).
59th Place — 2025 ICPC ECPC Qualifications Collegiate Programming Contest
ICPC ECPC Qualifications
Recognized for competing in one of Egypt's largest collegiate programming competitions, successfully solving challenging algorithmic and data structure problems under intense contest rules.
Certificates
Machine Learning and AI Diploma
AMIT Learning
Mobile Application Development Using Flutter
ZA TECH