Based in Cairo, Egypt — Building beautiful ML and AR experiences
Hey there! I'm Malak Alaa Mohamed, an energetic AI Engineer, Computer Vision Enthusiast, and Mobile AR Specialist from Cairo, Egypt 🇪🇬.
I thrive on building machine intelligence that matters—solving real problems with tech & a lot of imagination.
🎓 B.Sc. Artificial Intelligence | Helwan University | Expected 2026 – GPA: 3.68/4.00
- 🔎 Focus: Computer Vision (YOLO, Segmentation, FaceNet), AR, Deep Learning, Mobile ML
- 🚀 Interests: CultureTech, Automation, AR/VR, MLOps, Mobile/Edge AI
- 👑 Known for: Full-stack AI pipelines, research, visual storytelling, and team spirit
- 🌍 Fluent: Arabic • English • French
|
|
Computer Vision: YOLO, SAM-2, FaceNet, Segmentation, Image Processing ML/AI: Deep Learning (CNNs, RNNs), Scikit-learn, Generative AI, NLP Mobile & AR: Dart/Flutter, CV integration, AR frameworks Tools: Python, Docker, Git, Pandas, SQL, Streamlit, Matplotlib Soft: Tech Leadership, Research, Multilingual Communication, Teamwork |
💡 Fun Facts about Me:
• I’m obsessed with digitizing and preserving culture—my dream is an AR app that brings ancient monuments back to life! • Hackathons are my jam; I love late-night ML experiments and code jams. • I can code and present in three languages, and enjoy mentoring others in AI and CV. • 25% of my game-changing ideas happen past midnight ☕ • I once built a neural net demo for a high school event—using candy as training data!
- 🎤 Public Speaker: Led workshops & talks at university and community meetups on AI for everyone
- 🛡️ Women in Tech: Active in diversity & inclusion programs—love to encourage young women in STEM!
- 🌱 Always Growing: Currently learning advanced AR frameworks & scaling ML pipelines for production
- 🧠 Favorite Quote: “The best way to predict the future is to invent it.”
| Repo/Project | Highlight & Impact | Technologies |
|---|---|---|
| TimeLens AR Guide | AR app for cultural sites; live CV-powered recognition & info overlays | Dart, Python, CV, AR, ML |
| Car Type Classifier | Fine-grained model—Stanford Cars dataset, robust DL | Python, Jupyter, PyTorch |
| Car Damage Detection | YOLO+SAM-2 for object/damage, AI-generated reports | Python, Jupyter |
| Customer Segmentation | Clustered & visualized segments using genetic algorithms | TeX, Python |
| ML Pipelines & Tools | Reproducible E2E ML pipeline—Docker + Jupyter | Python, Dockerfile |
| Facial Recognition | Full MLOps: dataset → FaceNet → deployment | Python, MLOps |
| Dates | Role & Place | What I Did |
|---|---|---|
| 07/2025–Now | ML Trainee, DEPI Microsoft | Deep learning & model deployment |
| 09/2025–10/2025 | ML Intern, GTC | Model lifecycle: data ➔ training |
| 08/2025–09/2025 | AI Instructor, IEEE Banha | Crafted & taught “AI Camp 2025” |
| 07/2024–09/2024 | ML Intern, Neurotrix | Data wrangling & dev teamwork |
| 07/2024–09/2024 | AI Intern, ITI Cairo Uni | Built real-world ML solutions |
| 07/2023–08/2024 | Intern, CIB Egypt | Digital innovation & comp. winner |
- 🥇 Winner, LinkedIn / Smart Village Competition (2023)
- 🇫🇷 DELF A1–B2 French Proficiency
- 🏅 Microsoft: Career Essentials in SW Dev
- 📈 DataCamp: Tree-Based Models, Supervised Learning
- 🪄 Meta: Frontend Dev
- 🎓 LinkedIn: Generative AI, AI-First Product Leader