Francisco Mendez is a Colombian-American researcher who has taken courses from MIT and collaborated with NVIDIA deep learning experts to explore how data-driven models can enhance human longevity, diagnostic precision, and accessibility in medicine. He is the author of “Strategic CBAM and Augmentation in EfficientNet-B0 for Skin Lesion Classification,” published in the National High School Journal of Science (NHSJS), where he developed a novel skin lesion classifier designed to improve diagnostic accuracy while remaining memory-efficient and deployable on limited hardware. His work demonstrates how optimizing neural networks for efficiency can expand access to diagnostic AI in low-resource clinical settings.

Francisco has also conducted research under PhD mentors from the University of Oxford and UC Berkeley and developed accessible AI projects such as Pose2Play, an AI-powered platform for rehabilitation and inclusion. He holds a professional credential in Data Science and Machine Learning from the MIT Institute for Data, Systems, and Society (IDSS), where he also earned top recognition as 1st Place in the MIT IDSS Shinkansen ML Hackathon (Hack Linguist Winner). Currently an International Baccalaureate Diploma Programme scholar at Lyford Cay International School, Francisco pursues Higher Level Mathematics, Physics, and Chemistry.

As founder and leader of his school’s Coding Club, Francisco empowers younger students to explore AI and computational mathematics. His mission is to design AI systems that provide critical insights into medical decision-making and promote a future where advanced healthcare technologies are safe, interpretable, and accessible to all.