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Amr is an ML engineer who studied at the German University in Cairo and focuses on translating real-world requirements into practical AI systems that balance reliability with user experience.
His work spans knowledge-graph-driven RAG pipelines and LLM-based generation, with a focus on accuracy, retrieval quality, and strong evaluation practices.
He recently completed a bachelor thesis titled “From Sources to El Da7ee7: A Graph-RAG Pipeline for Arabic Educational Script Generation,” exploring how AI can turn factual sources like Wikipedia into engaging, accurate Arabic educational scripts.
The pipeline combines semantic graph construction, dense retrieval, and fact-checked generation, then adapts the output into Egyptian Arabic with narrative prompts to preserve style and clarity.
He validated the system with both human and automatic evaluation, aiming for outputs that are factual, engaging, and ready for real-world audiences.
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