Egypt University of Informatics Partners with Dell for Three AI Graduation Projects in Healthcare and Traffic
Professor Ahmed Hamad, Acting President of the Egypt University of Informatics, announced a collaboration between the university and several global and local companies in the ICT sector. The partnership includes three significant graduation projects at the Faculty of Computer and Information Sciences in collaboration with Dell Technologies, targeting improvements in healthcare services and urban traffic management. This initiative aligns with the Ministry of Communications and Information Technology’s efforts to build AI capabilities in Egyptian universities.
Since its establishment in 2021, the university has focused on linking academic curricula, faculty research, and student projects with market needs, ensuring research outputs have practical and economic impact while bridging the gap between academia and industry.
Dean of the Faculty of Computer and Information Sciences, Dr. Hoda Mokhtar, highlighted that participation in the Ministry’s AI initiative helps train students and faculty to address real-world challenges in the ICT sector.
The collaboration includes a specialized faculty training program designed by Dell experts, covering five AI-driven focus areas: smart agriculture, intelligent urban transport, government service monitoring, digital healthcare diagnostics and treatment, and strategic growth for the digital economy. From these, students selected three graduation projects: two focused on healthcare services and one on improving traffic systems in Greater Cairo.
The first project, MedTwin, aims to tackle challenges in chronic disease management by providing continuous, personalized AI-based healthcare support through digital twin simulations and multi-agent intelligent systems.
The second project develops a smart medical assistant with dual interfaces: a patient-friendly version and a clinician-focused version. It interprets symptoms, analyzes medical images, supports clinical report preparation, and incorporates predictive modules for early detection and ongoing care.
The third project addresses chronic traffic congestion in Cairo. It aims to create an AI-powered urban planning assistant that simulates, analyzes, and optimizes proposed road network modifications using real city maps, traffic simulation engines, natural language planning models, and reinforcement learning techniques. This system acts as an intelligent collaborator for planners, providing evidence-based recommendations to improve urban mobility.
