Nouran
Hassan Hafez
AI Engineer · Software Developer · IEEE Researcher
I build intelligent systems that ship — from Ministry-funded medical AI to globally-recognised ML models. Final-year CS student turning research into real-world impact.
About Me
I'm Nouran Hassan Hafez — a final-year Computer Science student at Misr International University with a minor in Artificial Intelligence. I don't just study AI; I build production-grade systems with it.
My graduation project, Glucora, is funded by the Ministry of Scientific Research — a real AI medical platform for continuous glucose monitoring and automated insulin delivery. My IEEE-published research on e-commerce behaviour prediction analysed 285 million events and reached 96% accuracy.
I ranked Top 5 globally at Microsoft's MLSA Demo Day, worked as a software developer for a Canadian tech firm, and hold certifications from Stanford, IBM, NVIDIA, and Oracle.
"I bring the rare combination of deep ML research expertise and full-stack engineering — I can take an idea from a Jupyter notebook all the way to a deployed, production mobile app."
Experience
Every role sharpened a different edge — research, engineering, finance, and global leadership.
Projects
Awarded, published, and shipped — building things that actually matter.
Glucora — AI Continuous Glucose Monitoring & Automated Insulin Delivery
My most important project. An end-to-end AI medical platform: GRU/LSTM/HMM pipeline for 30-minute blood glucose prediction, production Flutter app with multi-role access, real-time AI clinical recommendations, automated insulin delivery, multilingual support across 7 languages, and a 23-table PostgreSQL backend with row-level security.
Chef's Whispers — AI Recipe Recommender
Azure OpenAI + LangChain recipe system. Presented live to 100+ attendees, featured in a Microsoft blog. React.js + Azure Functions full-stack.
GitHubSoundSpot Music Platform
Full Spotify-inspired streaming platform with playlists, chatbot, and admin dashboard. Node.js + MongoDB MVC architecture.
GitHubMegaMinds Course Recommender
Academic programme recommendations based on student interests and performance using collaborative and content-based filtering.
GitHub
eCommerce Behaviour Prediction
285M+ events. GRU & Transformer models. 96% accuracy. The research behind my IEEE paper.
GitHub
Musical Instrument Detection
5 CNN architectures on audio spectrograms. 98% accuracy via transfer learning and fine-tuning. GoogLeNet & MobileNet best performers.
GitHub
Healthcare Test Results Classification
XGBoost at 88% accuracy classifying normal vs. abnormal test results. Full PCA, ensemble, and hyperparameter tuning pipeline.
GitHubResearch
E-Commerce Customer Behaviour Prediction
Led a research team analysing ~285 million real-world e-commerce event sequences to predict user actions over time — view, add-to-cart, purchase. Benchmarked Random Forest, XGBoost, LSTM, GRU, Transformer, and TCN models with full hyperparameter tuning. GRU and Transformer architectures achieved 96% accuracy, outperforming all ML baselines.
Education
Ready to build something extraordinary?
I'm actively looking for full-time AI and software engineering roles. I bring IEEE-level research depth, production-grade engineering, and the drive to make things that actually matter. Let's talk.