Yiping Wang

Yiping Wang will be pursuing a master’s degree under the supervision of Professor Yuri Boykov. His main research interests are in computer vision and machine learning to analyze medical images.

After watching a 2015 TED lecture titled “How we’re teaching computers to understand pictures” by computer vision expert Fei-Fei Li, Yiping became captivated in understanding how computers extract and learn meaningful information from vast databases of photos. Given enough training data, computers can learn to reliably identify commonplace objects in photos — for example, a cat, tree, or car — with great accuracy, but can they also be trained to analyze medical images and be used in clinical settings to assist medical professionals?

During his undergraduate degree, Yiping worked as a research intern at the University of British Columbia, where he proposed a simple but effective transfer learning algorithm to classify ovarian cancer histopathology — an algorithm that was able to outperform doctors without gynecological training. He also worked as a research intern at Imagia, a Montreal-based company that explores applications in computer vision and mapping of clinical information, where he helped develop a novel recurrent generative adversarial network algorithm to synthesize high-resolution 3D CT scans.

During his graduate studies, Yiping plans to enhance and expand his understanding of computer vision, especially segmentation. He is particularly enthusiastic about developing weakly supervised segmentation algorithms to segment cells in high-resolution histopathology images, and to combine single-cell sequencing to improve patient care and solve real-world clinical problems.

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