Jingying Wang receives Rackham Barbour Scholarship

CSE PhD student Jingying Wang has been selected to receive the Barbour Scholarship in recognition of her academic accomplishments. Part of the Rackham Predoctoral Fellowship program, the Barbour Scholarship was endowed by Levi Lewis Barbour in 1917 to support female doctoral candidates from countries in Asia who demonstrate outstanding academic and professional achievements in STEM fields.

The scholarship will support Jingying’s continued research leveraging artificial intelligence (AI) and augmented reality (AR) technologies to enhance surgical training. Specifically, her doctoral work focuses on developing human-AI systems that allow for and improve video-based surgical training through computer vision techniques, textual and visual feedback mechanisms, and intraoperative behavior analysis. 

Wang’s doctoral research addresses critical gaps in current medical education by introducing AI-powered tools designed to create more interactive and effective learning experiences for surgical trainees. Her pioneering platform, Surgment, uses advanced image segmentation techniques to convert surgical videos into interactive teaching tools. The platform allows attending surgeons to pinpoint key learning opportunities and provide visual feedback directly within surgical videos, helping to alleviate time constraints while also improving educational outcomes. For more information about Surgment, please see this previous CSE article. 

In addition to Surgment, Jingying’s paper “Looking Together ≠ Seeing the Same Thing: Understanding Surgeons’ Visual Needs During Intra-operative Coordination and Instruction” won a Best Paper Honorable Mention at CHI 2024 . Both this study and her work on Surgment were central to  a $1.2 million NSF grant aimed at furthering the development of these surgical training tools. Through this funding, Jingying and her collaborators are working to explore new techniques to analyze and enhance surgical training, including real-time AR visualizations and AI-assisted debriefing dashboards.

Beyond her research accomplishments, Jingying is deeply committed to mentorship, and has received outstanding feedback for her dedication and teaching effectiveness as a graduate student instructor. 

“Jingying does not go after easy problems,” said Prof. Xu Wang, her advisor and nominator. “Her dissertation topic on using AI to support surgery training and collaboration between attending surgeons and residents is uniquely challenging in that it connects several disciplines, including human-computer interaction, computer vision, mixed reality, medical technologies, and surgical science. I’m very proud of what she has achieved in the past three years, and I’m keen to see what she’ll come up with next.”

With the support of the Barbour Scholarship, Jingying will further pursue her work developing scalable AI systems to provide educational opportunities for medical trainees, with the aim of enhancing how surgical skills are taught and advancing patient care and safety.