Matthias Christian Lutz

Bio

I am a medical student at the Technical University of Munich and a Student Researcher at the Stanford Mussallem Center for Biodesign, where I conduct my doctoral research under the supervision of Dr. Paul Schmiedmayer. My work is centered at the intersection of artificial intelligence and medicine, with a strong focus on translating advanced machine learning approaches into clinically meaningful applications.
At Stanford, my research focuses on cardiovascular medicine, where I develop personalized, multimodal large language model (LLM)-based systems to detect early progression of Cardio-Kidney-Metabolic (CKM) disease and support more precise, data-driven clinical decision-making. By integrating electronic health record data, wearable time-series signals and patient communication, my work aims to create explainable, guideline-aligned AI systems that deliver personalized feedback and smart nudges. The overarching goal is to strengthen health literacy, improve patient activation and enable earlier, more effective prevention of cardiometabolic disease progression.
I ranked among the top 1% nationwide in Germany’s first written medical licensing examination and gained over two years of experience at Brainlab in Clinical Affairs, where I contributed to international clinical trials and regulatory processes in the MedTech sector. These experiences shaped my interest in translational research at the interface of clinical practice, technology development, and implementation.
Beyond my research I am the co-founder and previous chair of OneAIM (one-aim.org), a student-led MedTech initiative that has grown into the largest organization of its kind in Germany, connecting over 500 students across medicine, engineering and computer science through interdisciplinary innovation programs. In parallel, I am actively involved in shaping medical education: As the only student member of the curriculum commission at the Technical University of Munich, I play a leading role in integrating digital medicine into the medical curriculum. I also served as the instructor for the elective course “Neural Networks - AI in Medicine” at LMU Munich, introducing students to the intersection of clinical medicine and artificial intelligence.
My broader goal is to advance clinically grounded, explainable AI systems that not only improve decision-making but also empower patients and physicians, bridging the gap between technological innovation and real-world healthcare impact.