📄 My CV

You can view my CV directly below or download it for later.

Sayed Gamal

Cairo, Egypt | 📞 +201093521404 | ✉️ sayedgamall@outlook.com

🔗 LinkedIn | 🖥️ GitHub

Bachelor’s degree in Computer Engineering and Control Systems
Mansoura University (Sep 2020 – Aug 2025)

Fine-tuned a YOLO11 model on a RoboFlow smoke-fire dataset, achieving mAP@50 of 0.77.
Engineered a real-time alert system optimized with multithreading for rapid smoke and fire detection.
Integrated multi-channel notifications using Telegram Bot and WhatsApp via CallMeBot.
Designed a test suite to validate system reliability, ensuring real-time detection and reporting.

Fine-tuned a pre-trained ResNet101V2 model for accurate classification of 15 parasite species.
Applied image augmentation techniques to improve the model’s robustness and generalization.
Optimized model performance using dynamic learning rates, early stopping, and class-weight adjustments, reducing overfitting and addressing class imbalance.
Containerized the solution with Docker for consistent deployment across diverse environments.
Deployed an interactive application using Streamlit, hosted on Azure Web App Service for cloud accessibility and real-time testing.

Developed an end-to-end customer churn prediction system leveraging advanced ensemble models (XGBoost, LightGBM, CatBoost).
Delivered actionable insights to enhance customer retention through innovative data analysis and visualization.
Built a Flask-based web application for real-time churn prediction, integrating intuitive UI and pre-filled sample data functionality for seamless user experience.
Deployed containerized application using Docker, ensuring scalability, easy integration, and smooth deployment across various environments.

Conducted EDA for feature selection, visualizing insights with Matplotlib and Seaborn.
Built data cleaning and preprocessing pipelines with Pandas to prepare input data for modeling.
Developed and fine-tuned ML models in scikit-learn, optimizing with cross-validation and hyperparameter tuning.
Created an end-to-end pipeline from raw data to predictions.
Deployed models with Flask and Django, providing a user-friendly interface in production.

Led a team to enhance the student activity’s public image at Mansoura University.
Planned, executed, and managed 6 major events, significantly boosting engagement and visibility.
Organized “The Way to Distribution 2.0” event with Eduneers Construction, introducing students to advanced distribution and automation techniques.
Managed “Stark Lab” summer camp, training over 200 participants on various technical tracks.
Coordinated the “Stark Expo” event, featuring industry speakers and attracting over 300 attendees.
Secured sponsorships and partnerships, increasing social media followers by 20% and doubling recruitment applications.

Developed and delivered workshops on data cleaning and linear algebra, receiving positive feedback for clarity and practical value.
Led weekly sessions applying data science concepts to real-world projects, enhancing hands-on learning and application.
Sourced and developed comprehensive study materials and mini roadmaps for team members, empowering them with the knowledge necessary to excel in data science projects.
Mentored and supported over 20 members, tracking their progress and providing tailored guidance to improve their performance in data science projects.

Programming Languages: Python, C, C++, MATLAB, SQL
Problem Solving: Data structures, algorithms (450+ problems solved on LeetCode and Codeforces)
Data Manipulation & Visualization: Pandas, NumPy, Seaborn, Matplotlib, OpenCV
Web Scraping: Beautiful Soup, Scrapy
Machine Learning Frameworks: Scikit-learn, TensorFlow-Keras, PyTorch, Hugging Face
Version Control: Git, GitHub
Deployment & Development: Docker, Streamlit, Flask, Django