Xingyu's research focuses on building more reliable and safer intelligent systems, with a strong drive to leverage AI and machine learning for impactful healthcare innovations.

Xingyu's research interests are centred on machine learning, computer vision, and their applications for structured/unstructured data analysis with the ultimate goal of developing novel techniques to build intelligent systems that are more reliable and safer. In addition to Xingyu's pursuits in trustworthy AI, she is also keen on leveraging AI and machine learning for healthcare-focused innovations.

She is an assistant professor in the Department of Electrical and Computer Engineering at the University of Alberta. She received her MSc in electrical and computer engineering from the University of Alberta and her PhD in the same subject from the University of Toronto. Before joining the University of Alberta, Xingyu was a postdoctoral fellow at the University of Toronto and a postgraduate affiliate of the Vector Institute for Artificial Intelligence. Besides academia, Xingyu also worked in industry as a video algorithm engineer.

Xingyiu's research focuses on computer vision, data analytics and health informatics. Her research outcomes have contributed to projects involving computational medical imaging, cranial implant design, genomes for COVID-19, and security in deep learning.

In addition to her work with the U of A and Amii, Li is a member of AI4Society, the Cancer Research Institute of Northern Alberta, and The Women and Children’s Health Research Institute.