Dr. Zi Yang is a distinguished medical physicist renowned for his innovative contributions at the intersection of artificial intelligence and radiation oncology. He currently serves as Clinical Assistant Professor in the Department of Radiation Oncology at Stanford University where he specializes in radiation physics with a focus on advancing medical imaging and treatment technologies. His academic journey has positioned him at the forefront of developing computational approaches to enhance precision cancer care through sophisticated image analysis and treatment planning systems. Dr. Yang actively contributes to the education of future medical physicists through his teaching of experiential learning courses in medical physics at Stanford. His leadership in translating computational advances into clinical applications has established him as a rising figure in the field of medical physics.
Dr. Yang's groundbreaking research has pioneered novel methodologies for radiotherapy dose prediction using advanced segmentation networks significantly improving the accuracy and efficiency of GammaPod planning for precision radiation delivery. His development of the global binary mask approach for structure segmentation in medical images has provided the field with a powerful tool for enhancing tumor targeting while minimizing radiation exposure to surrounding healthy tissues. His innovative work on predicting real-time three-dimensional deformation field maps using Volumetric Cine MRI represents a major advancement in adaptive radiation therapy enabling more precise tumor tracking during respiratory motion. These contributions have substantial clinical implications for improving treatment outcomes for patients with liver cancer and other malignancies requiring precise radiation targeting. The integration of artificial intelligence with medical physics principles in his research has established new paradigms for personalized radiation treatment planning.
Beyond his technical contributions Dr. Yang has become an influential voice in shaping the future direction of AI applications in medical physics through his active participation in professional communities and educational initiatives. His mentorship of students and trainees in medical physics focuses on equipping the next generation with both computational expertise and clinical understanding necessary for advancing precision oncology. Current research directions in his laboratory emphasize the development of robust AI systems capable of real-time adaptation during radiation delivery addressing critical challenges in motion management for abdominal and thoracic tumors. Dr. Yang's collaborative approach bridges engineering innovation with clinical practice working closely with radiation oncologists and medical physicists to ensure practical implementation of his methodologies. His ongoing work promises to further transform radiation therapy through increasingly sophisticated computational models that enhance treatment precision while improving patient quality of life during cancer care.
