AI Engineer · Machine Learning Engineer · Data Scientist · Software Engineer
Passionate about building AI systems, machine learning applications, LLM-powered solutions, and data-driven products that solve real-world business problems.
I design, train, and ship machine learning systems — from classical models to modern LLM and RAG pipelines. Currently studying Computer Science & AI at Ain Shams University, I work at the intersection of research, data, and product.
I'm a Computer Science & AI student focused on turning research-grade models into production systems people actually use. My work spans computer vision, NLP, LLM applications, and full-stack ML platforms — with an emphasis on measurable business impact.
I care about clean data, honest evaluation, and thoughtful UX around model outputs. I move fluently between Python notebooks, PyTorch training loops, backend services, and container deployments.
From low-level model engineering to production-grade backends, visualization, and team leadership.
A blend of engineering, leadership, and community impact.
A mix of applied ML, deep learning research, LLM systems, and full-stack data products.
Founder / Product Builder
Analytics solution for Egyptian startup founders to track customer retention, repeat purchases, and growth signals.
Helps founders turn customer behavior into actionable retention and revenue insights.
AI Product Contributor
AI-powered telemedicine platform with an Arabic medical chatbot named ودود for symptom triage and clinic workflow support.
Brings conversational AI and digital triage support into an Arabic healthcare context.
Initiative Lead
Initiative designed to guide university students toward active civic participation, leadership, and meaningful academic achievement.
Connects student growth, leadership, and real-world engagement beyond the classroom.
Data Science & ML Engineer
End-to-end customer intelligence platform using K-Means clustering, 23-feature data preparation, and six classification models for buyer segmentation and business analysis.
Achieved 99.55% accuracy with Logistic Regression and demonstrated a full data-to-product workflow.
Deep Learning Researcher
Facial emotion recognition project using advanced vision models including ViT, DeiT, and CNN-based architectures for accurate classification.
Reached 1st place in a Kaggle competition and showed strong deep-learning and CV execution.
ML / Analytics Builder
Dual-task prediction system for vitamin deficiency severity and related condition categories using feature engineering, model tuning, and explainable ML workflows.
Combined regression and classification to support practical health-data decision making.
AI Systems Builder
Built an automatic differentiation engine from scratch, including computational graphs, backpropagation, tensor operations, and custom training logic.
Demonstrates a strong understanding of the mechanics behind modern deep-learning frameworks.
ML Foundations Builder
Implemented Perceptron and Adaline models from scratch with preprocessing, feature scaling, one-hot encoding, and decision-boundary analysis.
Strengthens fundamentals in model logic, optimization, and data preparation.
Place — Kaggle Emotion Detection Competition
Retail Buyer Segmentation Accuracy
Vision Transformer Accuracy
CNN Validation Accuracy
Faculty of Computer Science and Artificial Intelligence
NTI · Ministry of Communications and IT
View Certificate
Competitions, hackathons, IEEE, NASA Space Apps, UN Habitat, and conferences.
I'm open to full-time roles, internships, research collaborations, and freelance ML work.