Ying Ding

Dr. Ying Ding serves as the Bill & Lewis Suit Professor at the School of Information, University of Texas at Austin, with a joint appointment in the Department of Population Health at Dell Medical School. She co-chairs the AI Health Lab, bridging information science and clinical medicine to advance AI applications in healthcare. Previously, she was a professor and director of graduate studies for the data science program at Indiana University's School of Informatics, Computing, and Engineering.

Her research spans AI in healthcare, knowledge graphs, semantic web technologies, and the science of science. She has pioneered work in applying graph mining techniques to drug discovery and pandemic response, particularly through her development of the PubMed Knowledge Graph and analysis of COVID-19 research dynamics. Her work integrates computer vision, natural language processing, and knowledge representation to address healthcare challenges.

Dr. Ding has published over 240 papers and secured funding from NIH, NSF, and European Union projects. She co-edits the Semantic Web Synthesis book series and serves as co-editor-in-chief for Data Intelligence published by MIT Press. Her research has been featured in Nature and The Atlantic, particularly her work on research novelty during the pandemic.

• Amazon Machine Learning Research Award (2020)
• World's Top 2% Scientists 2020 by Stanford University
• Top 20 most read JASIST paper (2017-2018)
• Top 25% cited PLOS Computational Biology articles (2017)

As an educator, she teaches courses on AI in Health and Data Semantics, emphasizing hands-on learning with real-world healthcare data. She has organized major conferences including The Web Conference 2023 in Austin and multiple Generative AI for Healthcare workshops at NeurIPS. She is also the co-founder of Data2Discovery, a company advancing AI technologies in drug discovery and healthcare.