I'm a Computer Engineer with an M.S. in Computer and Communication Engineering, working across software development, artificial intelligence, and computer vision. My background spans building practical, real-world systems and doing academic research in deep learning — I like being equally comfortable shipping a working application and writing up a rigorous experimental study.

• 🎓   M.S. in Computer and Communication Engineering, and a B.S. in Computer Engineering, from LIU University
• 💻   Solid foundation in software engineering, algorithms, and problem-solving, across desktop, web, and mobile
• 🧠   Research background in deep learning and computer vision, with a focus on Genetic Algorithm-based optimization
• 📱   Experience building and maintaining cross-platform mobile apps with Flutter and Dart
• ⚙️   Experience with C++ systems-level work — memory management, linking, debugging, and third-party library integration
• 🌐   Comfortable across the full stack, from PHP/MySQL backends to React/Node.js based web apps
• 📄   Published and peer-reviewed research author, with work appearing in IEEE Xplore and an AI/ML journal
• 🗣️   Fluent in Arabic, English, and French

• Intelligile (2025) — Built foundational C++ skills through debugging, linking, and third-party library integration, along with systems-level troubleshooting (memory management, dependencies, OS interactions).
• NevyBits (2024) — Developed and maintained cross-platform mobile applications with Flutter/Dart, building responsive UI components and animations, and participated in regular code reviews.

My graduate research focuses on deep learning, applying architectures like YOLOv12s, ResUNet++, and ResNet50, enhanced with Genetic Algorithm-based hyperparameter optimization, to build and evaluate high-performing computer vision models.

• 📖   High-Performance Brain Tumor Detection in MRI Using YOLOv12s: A Comparative Study — Proceedings of ICIICE 2026, IEEE Xplore
• 📖   Dual-Task ResUNet++ with Genetic Algorithm Hyperparameter Optimization for Brain Tumor Segmentation and Classification — accepted, Applied Artificial Intelligence and Machine Learning (AAIML) Journal

• 🧠   Master's Thesis — Brain Tumor Detection and Classification — Deep learning frameworks combining detection, segmentation, and classification, evaluated on public brain MRI datasets against state-of-the-art models.
• 📝   NotePilot — A Flutter-based desktop notes app that integrates AI capabilities via the OpenAI API, for creating, managing, and organizing notes and prompts.
• 💊   Multi-Pharmacy Management System — A client–server project with a PHP backend and an HTML/CSS/JavaScript frontend built with Bootstrap, for managing multiple pharmacy branches.
• 🩸   Blood Bank Management System — A Java Swing desktop application for managing donors, blood inventory, and requests.

📫   Reach out via GitHub or LinkedIn — always happy to talk software, systems design, or ML research.