Ying Ding, Ph.D.

Ying Ding, Ph.D., is a courtesy professor in the Department of Population Health and the Bill and Lewis Suit Professor at The University of Texas at Austin School of Information.

Before that, she was a professor and director of graduate studies for the data science program at the School of Informatics, Computing and Engineering at Indiana University. She has led the effort to develop the online data science graduate program for Indiana University. She also worked as a senior researcher at Department of Computer Science at the University of Innsbruck (Austria) and Free University of Amsterdam (the Netherlands).

Her research focuses on AI in health by developing and adapting existing machine learning and deep learning methods about graph mining and computer vision to solve the problems related to health care and drug discovery. She collaborates with faculty and researchers from Mount Sinai Hospital in New York to apply contrastive learning on patient electronic health record data for risk prediction. She also works with colleagues from Cornell Medical School in New York on medical imaging diagnosis and radiology report generation from chest X-ray images based on deep learning methods from computer vision and natural language processing. She collaborates broadly with researchers from pharmaceutical companies and colleagues from the Department of Computer Science and the Department of Electrical and Computer Engineering at UT Austin to develop deep graph mining methods on large scale knowledge graphs to enable better drug discovery.