about_me = {
"name": "Dina Hussam",
"home": "Cairo, Egypt",
"education": "BSc in Systems and Biomedical Engineering, Cairo University",
"graduation_year": "2024",
"gpa": "3.45 (Very Good)",
"role": " Full-Stack Developer | Teaching Assistant | AI Engineer",
"languages": ["Arabic", "English", "German"],
"hobbies": ["AI Research", "Healthcare Tech", "Graphic Design", "Chess", "Travel"]
}
Passionate Software Engineer with a strong background in Biomedical Engineering and hands-on experience in Full-Stack DevelopmentMachine, Learning and Deep Learning.
I specialize in building AI-powered healthcare solutions, from medical imaging to rehabilitation systems and intelligent chatbots.
I've worked on real-world projects involving BCI (Brain-Computer Interface), FES, medical diagnostics, and MLOps, and I'm currently contributing as a Software Engineer at ET3 and a Teaching Assistant at Cairo University.
Python |
Java |
C++ |
JavaScript |
Dart |
HTML |
CSS |
PyTorch |
TensorFlow |
Scikit-learn |
Keras |
OpenCV |
Pandas |
NumPy |
Django |
React |
Flutter |
Android Studio |
PostgreSQL |
MySQL |
Docker |
Git |
GitHub |
GitLab |
Qt |
Power BI |
JSON |
Matplotlib |
- 🥇 1st Place – Final Project | Konecta AI/ML Internship (2025)
- 🥉 3rd Place – Ebda3(12) Competition for University Students (2024)
- 📜 Supervised Machine Learning: Regression & Classification – Coursera
- 📜 AI Diploma – Beta Academy
- 📜 Data Analysis Challenger Track – Udacity
- 📜 Algorithmic Toolbox & Data Structures – Coursera
| Project | Description | Tech Stack |
|---|---|---|
| Hand Rehabilitation System with BCI & FES | AI-driven EEG classification to trigger FES for hand movement restoration. | Python, Keras, BrainDecode, PyQt, Firebase, Raspberry Pi |
| DinoPay – Cross-Platform Digital Wallet | Secure mobile/web wallet with payments, transfers, KYC, and analytics. | Flutter, React, Django, PostgreSQL, ETL |
| AI-Based Ovarian Cancer Subtype Diagnosis | Dual-model AI system for biopsy sample classification (98.74% accuracy). | TensorFlow, Flask, OpenCV, Scikit-learn |
| DINO Telecom Chatbot | Intelligent customer-service chatbot with LangChain & Gemini 2.5 Flash. | Python, LangChain, Gemini API, Flask |
| Screening Mammography Breast Cancer Detection | Deep learning model for DICOM image classification (99% accuracy). | TensorFlow, Keras, DICOM Processing |
