Hana Nassef

Data Scientist & Published AI Researcher

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About Me

Hana Nassef

Hello, I'm Hana!

I'm a Computer Engineer with a strong focus on Machine Learning and Data Science. I enjoy turning data into insights and building intelligent systems that solve real-world problems. Through internships at Huawei and e& Egypt, I've worked on data preprocessing, model training, web development, and network performance analysis.

Alongside my technical journey, I have a deep passion for teaching. I'm also a co-author of an IEEE-published paper and have recently published in a Q1 Journal, contributing research that reflects my curiosity and commitment to learning. My goal is to continue growing as an engineer, educator, and problem solver.

Contact Me

Education & Certifications

Nile University

Graduated: Jan 2026

Bachelor of Science in Computer Engineering.

GPA: 3.86 / 4.0 (Highest Honors)

Full scholarship recipient from Bank Misr.

Digital Egypt Pioneers Initiative (DEPI)

In Progress

Specializing in Data Science and freelancing strategies, supported by the Egyptian MCIT.

ALX Africa

Graduated

Completed an intensive 14-month program in Data Science with a focus on professional soft skills.

Nile Egyptian School

Graduated with Honors

Achieved a perfect score (Straight A*s) in the Cambridge International curriculum.

Skills

Data Analysis & Visualization

  • Data wrangling & statistical analysis
  • ETL processes
  • Interactive dashboards with Power BI
  • Matplotlib & Seaborn

Machine Learning & AI

  • Model development & evaluation
  • Feature engineering
  • Federated Learning
  • Deep Learning (CNNs, NLP)

Programming

  • Python, C++, SQL, Verilog
  • Scikit-learn, Pandas, NumPy
  • Object-Oriented Programming

Hardware & Systems

  • Digital logic design
  • Computer architecture
  • Parallelization with OpenMP
  • FPGA design with Vivado

Tools & Deployment

  • Docker & Containerization
  • W&B Experiment Tracking
  • Flask API Development

Research Writing

  • Peer-Reviewed Publications
  • Technical Documentation (LaTeX/Overleaf)
  • Literature Review & Gap Analysis
  • Methodology Design & Validation

Research & Publications

Featured

AuraViT-FL: A Resource-Efficient 2D Hybrid Transformer Framework for Federated Lung Tumor Segmentation

Published in Machine Learning & Knowledge Extraction (MDPI) — Q1 Journal

A novel framework leveraging hybrid transformers and federated learning to enhance lung tumor segmentation accuracy while ensuring data privacy and resource efficiency.

Read Paper

Intelligent Smart Home System: Secure Solution for Enhanced Efficiency and Comfort

Presented at 2024 International Conference on Future Telecommunications and AI (IEEE) — IEEE Conference

Designed a state-of-the-art smart home security system using Arduino and TinkerCad. The system integrates face recognition, automated lighting, and weather-based fan control to balance low-power technology with robust security.

Read on IEEE Xplore

My Projects

AuraViT-FL Segmentation

AuraViT-FL

A resource-efficient hybrid transformer framework designed for privacy-preserving medical imaging. It enables multi-institutional federated learning for precise lung tumor segmentation on CT scans, eliminating the need to share sensitive patient data while maintaining near-centralized accuracy.

Federated Learning Medical Imaging Hybrid Vision Transformers
View Code View Paper
Production Book Recommendation System

Book Recommendation System (v2.0)

A production-ready ML service featuring a weighted TF-IDF engine and Dockerized Flask API. It includes automated model training and experiment tracking via Weights & Biases (W&B).

Docker MLOps W&B Tracking N-Grams
View on GitHub
Network Fault Detection

Network Fault Node Detection

Built a machine learning pipeline to detect and predict fault nodes in a simulated network. Conducted model benchmarking, selected top-performing algorithms, and improved results through hyperparameter tuning and ensemble learning to achieve optimal accuracy.

Python Scikit-learn Ensemble Learning
View on GitHub
Mini Projects

Mini Projects

A collection of academic and experimental projects showcasing foundational skills in Machine Learning, Data Visualization, and Hardware Design.

NLP Data Viz C++ Verilog

Professional Journey

Math & IGCSE Teaching Assistant

2019 – Present

Support secondary students in Mathematics and Sciences by preparing practice materials, assisting in lessons, and providing one-on-one guidance.

Nile University

2023 – 2024

Junior Teaching Assistant for undergraduate engineering courses, assisting professors, supporting labs, and helping students understand complex concepts.

e& Egypt

Aug 2024

Intern in AI & Web Development, focusing on data preprocessing for ML models and building a prototype full-stack application.

Huawei

Sep 2024

Back office & RQA Intern, learning network KPIs, monitoring performance, and shadowing engineers in live site upgrades from 2G to 4G.

Services I Offer

Whether you need help with a complex dataset, academic research, or a dedicated tutor, here's how I can contribute to your success.

Data & ML Services

  • Dataset Cleaning & Preprocessing
  • Advanced Feature Engineering
  • Interactive Dashboard Creation
  • Machine & Deep Learning Models

Research Assistance

  • Literature Review & Gaps Analysis
  • Technical Writing (LaTeX/Overleaf)
  • Methodology Design & Validation
  • Paper Formatting & Editing

Tutoring Services

  • Maths & Physics (School/Uni Level)
  • ICT & Computer Science
  • Core Engineering Concepts
  • Data Science Fundamentals