About

Kaveh Mozafari, MD, M.Sc., is a physician with a strong interest in surgery, surgical outcomes, and the thoughtful use of AI to support clinical decision-making and improve healthcare processes. His academic path, spanning astrophysics, pure mathematics, applied mathematics, neuroscience, epidemiology, and medicine, provides him with a broad and analytical foundation for addressing challenges in surgical care. Kaveh has participated in clinical environments across Canada and the United States, where he developed a deep appreciation for the structure, precision, and teamwork that define surgical practice. These experiences strengthened his interest not only in surgery itself but also in understanding how workflow, communication, and system design shape patient outcomes. His research includes work in surgical case analysis, oncology, immunology, and mathematical modeling. More recently, he has focused on how artificial intelligence can support surgical teams by streamlining reporting, reducing information delays, and enhancing overall efficiency. His approach prioritizes practical tools that respect the realities of clinical environments. Kaveh also has many years of experience teaching math, physics, biology, and medical sciences. He enjoys simplifying complex ideas and supporting learners at different stages of their training. Combining science, medicine, and process improvement, Kaveh works with humility, curiosity, and a genuine desire to contribute meaningfully to surgery, patient care, and the evolving role of AI in healthcare.