New Highlights

New Papers in Progress

  • Please check our new paper whether pandemic can reshape science and drive more innovations, and will scienists become more creative during the pandemic
  • please check out our attribute2vec paper at It is the deep learning algorithm which can consider the attributes of your knowledge graph
  • Our edge2vec can address the heterogenity by considering the edge semantics of your knowledge graph
  • Please check our paper about the evolution of COVID-19 misinformation in China by analzying 3 million weibo data

Co-editing Journals/Book Series/books

Past Events

Ying Ding

Ying Ding, Ph.D.

AI Health Lab

Bill & Lewis Suit Professor
School of Information
University of Texas at Austin

Department of Population Health
Dell Medical School
University of Texas at Austin

Google Scholar, LinkedIN

Contact Information

Mailing Address:
School of Information, ST STE 5202
University of Texas at Austin
1616 Guadalupe St, Austin, TX 78701-1204

Office: UTA 5.432
Tel: 512 471 3877

Research Interests

  • Explainable AI in Health
  • Data-Driven Science of Science
  • Knowledge Graph and Mining
  • AI in Healthcare and Drug Discovery
  • Medical Imaging Diagnosis: Computer Vision, Knowledge Graph, NLP
  • Semantic Web
  • Data-Driven Knowledge Discovery
  • Scholarly Communication
  • Team Collaboration


Co-Founder of Data2Discovery


Ph.D, Nanyang Technological University, Singapore