I am Mamdouh Radwan, a 12th-grade student at Dakahlia STEM School, driven by a deep interest in engineering, artificial intelligence, and real-world problem solving. Throughout my STEM journey, I have gained substantial experience in AI development, computer vision, embedded systems, IoT applications, mobile app design, and hardware–software integration, supported by hands-on work with Raspberry Pi, ESP32, ESP-CAM, sensing modules, and Flutter application development. My portfolio includes several major projects, most notably Light Headphones, an assistive AI device for visually impaired users that merges video analysis, obstacle detection sensors, and a dedicated mobile interface. I also developed EcoSkyRoof, an environmental innovation designed to reduce heat and improve air quality using recycled materials, alongside the Grey Water Removal (GWR) system, which aims to recycle household greywater through low-cost filtration technologies. In addition, I worked on an AI-based stellar exploration project that enables star identification and sky-mapping directly from Earth using machine learning and astronomical datasets. Beyond project work, I have actively participated in several national and international competitions, including NASA Space Apps, the IoT Challenge, ISEF-related school qualifiers, ITC, BioMed Tank, and the BCC Business Case Competition, where I strengthened my skills in research, analytical thinking, teamwork, and scientific presentation. Across these experiences, I consistently focus on designing impactful, feasible solutions that combine electronics, AI, and environmental innovation, and I aim to continue advancing in AI engineering and smart systems development to create technologies that serve communities and address real societal needs.

During my educational journey I participated in two NASA hackathons as part of the Ecoskyroof team, an interdisciplinary project that designs sustainable, low-cost roof systems using recycled materials to reduce heat and improve local air quality. Through these intensive hackathons I helped develop the concept from initial research and rapid prototyping to a working prototype, technical poster, and a polished pitch—efforts that earned our team Global Nominee recognition and propelled the project into ongoing development. The experience taught me how to apply scientific methods under tight deadlines, translate field and lab data into design decisions, and iterate quickly on materials and system architecture; I gained hands-on skills in environmental systems thinking, basic materials testing, prototype fabrication, and performance evaluation. Beyond technical abilities, the hackathons sharpened my teamwork and leadership: coordinating roles across design, data analysis, and presentation, managing time and resources, and communicating complex ideas clearly to judges and mentors. I also learned to use feedback constructively—integrating mentor critiques and user-centered testing to refine our solution for scalability and real-world constraints. Participating in these international challenges exposed me to project documentation best practices, formal competition judging criteria, and networking with students and professionals worldwide, and it strengthened my commitment to pursuing further research and engineering work focused on sustainable, community-centered technologies; the Ecoskyroof project remains active as we continue to develop prototypes, collect performance data, and prepare for the next stages of deployment and competition.

My educational experience through the ISEF competition with the Light Headphones project was intensely practical and deeply formative: as part of the ISEF track I researched and designed an assistive system that combines Raspberry Pi, ESP-CAM, distance and temperature sensors, AI-based video analysis, and a Flutter mobile app, then translated that design into working prototypes, test protocols, and a concise research presentation. We progressed from the ISEF stage and advanced to the national level, which exposed me to rigorous judging criteria and higher expectations for scientific method, reproducibility, and user-centered design. Throughout the process I learned how to define hypotheses, collect and annotate data for training computer-vision models, iterate hardware–software integrations under tight deadlines, and perform systematic user testing focused on accessibility needs. I also developed important soft skills: technical documentation and poster preparation, clear oral presentation to expert judges, teamwork and role coordination, time management, and responding to technical questions under pressure. The project sharpened my ability to bridge theory and practice—turning machine-learning models and sensor readings into reliable, real-world alerts—and it strengthened my commitment to building ethical, scalable assistive technologies that prioritize safety and usability.