Computer Vision is a field within artificial intelligence that is having significant impacts in medicine. Automated analysis of medical scan images can provide rich sources of insight and machine learning techniques to process this data open up a realm of possibilities for both researchers and clinicians. Dr. Nilanjan Ray is a leading researcher in computer vision, image analysis and visual recognition with deep learning. His current focus includes the application of cutting edge computer vision techniques to advance research in diabetes treatment. We talk about how he “accidentally” landed in this field, how computer vision works, the challenges of executing decision making using AI, how he is using generative adversarial networks to advance medical research (not for deep fakes!) and the role of technology in democratizing healthcare. “In order to make that kind of (diabetes) treatment available…there is almost no choice but to use AI to bring the costs down to scale up (delivery)” – Nilanjan Ray Dr. Nilanjan Ray is Professor of Computer Science at the University of Alberta. His research is in computer vision, image analysis and visual recognition with deep learning. His work includes medical imaging and general computer vision applications including classification, recognition, semantic segmentation, object tracking, image registration and motion detection. Dr. Ray has served as General Co-chair for AI/GI/CRV conference in 2017, Associate Editor for IEEE Transactions on Image Processing (2013-2017) and IET Image Processing (2016-), reviewer for NSERC DG and CRD grants.