I'm a Computer Science student passionate about Software Engineering, Data Science, and Problem Solving. I enjoy building full stack applications, solving algorithmic problems, and continuously learning modern software development practices.
I'm currently focused on strengthening my skills in ASP.NET Core, C#, Java, SQL Server, and AI fundamentals while working on real-world projects and preparing for software engineering internships.
- 💻 Software Engineering — clean architecture, OOP, SOLID principles, REST APIs, and backend development
- 🌐 Full Stack Development — ASP.NET Core MVC, HTML, CSS, JavaScript, Bootstrap, SQL Server
- 📊 Data Science & AI — Python, machine learning fundamentals, and data analysis
- 🧩 Problem Solving — C++, data structures, algorithms, and problem solving
- 🚀 Currently Learning — Software Design Patterns, System Design, and Cloud Technologies
Currently Looking For:
- Software Engineering Internships
- Backend Development Opportunities
- Open Source Contributions
- Collaborative Projects
| Area | Skills |
|---|---|
| 💻 Backend | ASP.NET Core MVC, ASP.NET Core Web API, C#, Entity Framework Core, REST APIs, LINQ, OOP, SOLID |
| 🌐 Frontend | HTML5, CSS3, Bootstrap, JavaScript, Responsive Web Design |
| 🗄️ Databases | SQL Server, MySQL, Database Design, SQL |
| 📊 Data Analysis | Python, Pandas, NumPy, Matplotlib, Data Cleaning, Data Visualization |
| 🤖 AI / Machine Learning | Python, Scikit-learn, Machine Learning Fundamentals, Model Evaluation, Data Preprocessing |
| 🧠 Programming | C++, Java, C#, Python, JavaScript |
| ⚙️ Tools | Git, GitHub, Visual Studio, VS Code, Postman |
| 🧩 Problem Solving | Data Structures, Algorithms |
🏡 SMSRLY – AI-Powered Property Recommendation Platform (Best Project in Group)
A full-stack real estate platform that connects tenants directly with property owners while delivering personalized property recommendations through a custom machine learning recommendation service. The project was developed as a graduation project under the Digital Egypt Pioneers Initiative (DEPI) and was recognized as the Best Project in the Group.
| Category | Details |
|---|---|
| Architecture | Three-Tier Architecture (Presentation, Business Logic, Data Access) |
| Backend | ASP.NET Core (.NET 10), Entity Framework Core, SQL Server |
| Frontend | React + Vite |
| Machine Learning | Python Recommendation Service |
| Infrastructure | Docker, Redis, Nginx |
| Authentication | JWT Authentication, BCrypt Password Hashing |
| Authorization | Role-Based Access Control (Admin, Owner, Tenant) |
| Features | Property CRUD, AI-Powered Recommendations, Swagger API, EF Core Migrations |
| Deployment | Docker/Podman Containerized Deployment |
| Recognition | 🏆 Best Project in the Group (DEPI Graduation Project) |
| Repository | View Repository |
- Designed and implemented a scalable three-tier architecture following clean architecture principles.
- Built secure authentication and role-based authorization using JWT and BCrypt.
- Developed RESTful APIs for property management and user operations.
- Integrated a Python-based machine learning recommendation engine with the ASP.NET Core backend.
- Containerized the complete application using Docker with Nginx as a reverse proxy.
- Documented and tested APIs using Swagger.
- Built a responsive React frontend communicating seamlessly with the backend services.
📡 Monitex — End-to-End Event-Driven IoT Monitoring & Anomaly Detection Suite
A distributed, event-driven IoT platform designed to bridge smart devices with intelligent analytics. Monitex leverages MQTT, AMQP, SignalR, and machine learning to enable resilient sensor data ingestion, real-time monitoring, and anomaly detection through a scalable microservices-inspired architecture.
| Category | Details |
|---|---|
| Architecture | Event-Driven Architecture, Clean Architecture, Repository Pattern |
| Backend | ASP.NET Core, SignalR, MQTT, RabbitMQ (AMQP) |
| Frontend | Angular |
| Databases | PostgreSQL, InfluxDB (Time-Series Database) |
| Edge Computing | ESP32, MQTT, mDNS (Avahi) |
| AI / ML | Python, Scikit-learn, Joblib, Anomaly Detection Pipeline |
| Infrastructure | Docker, Mosquitto, RabbitMQ, Nginx |
| Real-Time Communication | SignalR |
| Deployment | Fully Containerized with Docker Compose |
| Repository | View Repository |
- Designed a resilient event-driven architecture using MQTT and RabbitMQ for high-throughput sensor data processing.
- Developed scalable ASP.NET Core backend services following Clean Architecture and Repository Pattern principles.
- Built a real-time Angular dashboard powered by SignalR for live monitoring of devices and sensor telemetry.
- Integrated PostgreSQL for relational data and InfluxDB for efficient time-series storage.
- Developed a Python-based anomaly detection pipeline that analyzes historical sensor data and predicts abnormal events.
- Connected ESP32 edge devices to the platform using MQTT with automatic broker discovery through mDNS (Avahi).
- Containerized the complete ecosystem using Docker Compose, including backend services, frontend, AI service, RabbitMQ, Mosquitto, PostgreSQL, and InfluxDB.
- Implemented a reliable messaging pipeline that decouples data ingestion, processing, storage, and AI inference for improved scalability and fault tolerance.
Accord Business Group (ABG) | Jun 2026 – Sep 2026
Worked as a Software Engineering Intern, contributing to the development of enterprise web applications and backend services.
- Developed and maintained backend features using ASP.NET Core and C#.
- Built and consumed RESTful APIs following clean architecture principles.
- Worked with SQL Server and Entity Framework Core for database operations.
- Collaborated with the development team using Git and Agile practices.
- Participated in debugging, testing, and implementing new business requirements.
ASP.NET Core C# Entity Framework Core SQL Server REST APIs Git
Outlier AI | Sep 2024 – Mar 2025
Contributed to improving the mathematical reasoning capabilities of Large Language Models (LLMs) by evaluating, validating, and refining AI-generated solutions.
- Evaluated AI-generated mathematical solutions across various domains.
- Provided detailed feedback to improve model accuracy and reasoning quality.
- Solved advanced mathematical and logical reasoning tasks.
- Ensured high-quality outputs by following strict AI evaluation guidelines.
- Collaborated on projects focused on enhancing LLM performance.
Artificial Intelligence LLMs Mathematics Prompt Evaluation Problem Solving
Learning:
- System Design
- Spring Boot
- Angular & Sass
- Cloud Computing (Azure & Docker)
- Machine Learning & Data Analysis
Building:
- Full Stack Web Applications with ASP.NET Core & Angular
- AI-powered Software Solutions
- End-to-End Backend Systems
- Open Source Projects
Exploring:
- Distributed Systems
- Event-Driven Architecture
- Internet of Things (IoT)
- Large Language Models (LLMs)
Open To:
- Software Engineering Internships
- Junior Software Engineer Roles
- Backend Development Opportunities
- Open Source Collaboration
"Code is the closest thing we have to magic — engineer it with intention."