Yue Wang

Yue (Ray) Wang is an Assistant Professor at the School of Information and Library Science, University of North Carolina at Chapel Hill. He holds a PhD in Computer Science and Engineering from the University of Michigan, and prior degrees from Shanghai Jiao Tong University and Georgia Institute of Technology. His research focuses on text data mining, machine learning, and health informatics, with an emphasis on developing interactive and interpretable algorithms to reduce human effort in data analysis. He has contributed to clinical NLP, high-recall information retrieval, and computer-assisted qualitative analysis, winning awards such as the WSDM Best Paper Award (2016) and the Deborah Barreau Award for Teaching Excellence (2021).

Dr. Wang’s work bridges computational methods with real-world applications, including environmental policymaking through extreme systematic reviews and NeuroBridge—a platform for neuroimaging data discovery. He teaches courses like INLS 509 (Information Retrieval) and INLS 690-270 (Data Mining). His recent research explores user-centered explainability in AI, leveraging crowdsourced experiments and in-lab studies to understand how users interact with machine predictions. He collaborates with organizations like the EPA on machine-assisted literature screening for environmental policy.

• Education:
  • BS/BA in Information Security & English (Shanghai Jiao Tong University)
  • MS in Computer Applied Technology (Shanghai Jiao Tong University)
  • MS in Electrical and Computer Engineering (Georgia Tech)
  • PhD in Computer Science and Engineering (University of Michigan)

Awards:

• UNC Junior Faculty Development Award (2022)
• Outstanding Reviewer Award (WSDM 2022)
• Deborah Barreau Teaching Excellence Award (2021)
• WSDM Best Paper Award & Outstanding Reviewer (2016)
• Dow Distinguished Award (2015)

Key Research Themes:

• User-centric AI interpretability
• Health informatics applications
• Large-scale data screening for policy
• Explainable retrieval models