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Schedule Interview NowMy name is Youssef M. and I have over 3 years of experience in the tech industry. I specialize in the following technologies: Computer Vision, Deep Learning, OCR Software, AI-Enhanced Medical Imaging, NLP Tokenization, etc.. I hold a degree in Bachelor of Computer Science (BCompSc), Bachelor's degree. Some of the notable projects I've worked on include: AI-Powered CV Matching Engine MVP, AI Multi-Agent PDF Extraction System for Medical Data Processing, AI Dental Diagnosis: CNN-Based Teeth Classification System, RAG-Powered Nutrition QA System: Intelligent Dietary Assistant, Medical Report Validator using RAG and UMLS Embeddings, etc.. I am based in Cairo, Egypt. I've successfully completed 6 projects while developing at Softaims.
I am a business-driven professional; my technical decisions are consistently guided by the principle of maximizing business value and achieving measurable ROI for the client. I view technical expertise as a tool for creating competitive advantages and solving commercial problems, not just as a technical exercise.
I actively participate in defining key performance indicators (KPIs) and ensuring that the features I build directly contribute to improving those metrics. My commitment to Softaims is to deliver solutions that are not only technically excellent but also strategically impactful.
I maintain a strong focus on the end-goal: delivering a product that solves a genuine market need. I am committed to a development cycle that is fast, focused, and aligned with the ultimate success of the client's business.
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Cellula Technologies
Developed an intelligent CV matching system that ranks and explains candidate-job fit using semantic embeddings. Implemented a FastAPI backend with Hugging Face models, Supabase database, and cloud de
Built a sophisticated multi-agent AI system that transforms unstructured medical PDFs into structured data using specialized AI agents. Implemented three core agents: Validation Agent (data accuracy),
Developed an advanced computer vision system for automated dental condition classification from clinical images. Built custom CNN architecture achieving 92.3% accuracy across 6 dental categories (heal
Developed an intelligent nutrition question-answering system using Retrieval-Augmented Generation (RAG) architecture. Built comprehensive knowledge base with 10K+ nutrition documents, implemented FAIS
Developed a Retrieval-Augmented Generation (RAG) system to validate LLM-generated medical reports using ChromaDB and UMLS/SNOMED CT embeddings. Designed a FastAPI backend and built a feedback-ready UI
Bachelor of Computer Science (BCompSc) in
2020-01-01-2025-01-01
Bachelor's degree in
2017-01-01-2020-01-01