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Yue (Ray) Wang

Assistant Professor, UNC School of Information and Library Science

Yue (Ray) Wang




(919) 966-5042



Manning Hall - 7B

Yue (Ray) Wang


Text data mining, including related areas such as machine learning, information retrieval, natural language processing, social and information network mining, and health informatics.


BS (Information Security) and BA (English), Shanghai Jiao Tong University
MS (Computer Applied Technology), Shanghai Jiao Tong University
MS (Electrical and Computer Engineering), Georgia Institute of Technology, GT-Shanghai Campus, China
PhD (Computer Science and Engineering), University of Michigan, Ann Arbor


Dr. Yue Wang is interested in text data mining and machine learning with applications in health informatics. His dissertation focuses on developing principled interactive machine learning approaches that reduce human analysts’ information processing workload. His work is motivated by and applied to various data mining problems, including high-recall information retrieval, clinical natural language processing, and qualitative content analysis. He publishes in both computer science and health informatics venues, including KDD, SIGIR, WSDM, and JAMIA. He and his collaborators won first place in the TREC 2013 Microblog Track, and he received the Best Paper Award and Outstanding Reviewer Award in WSDM 2016.


INLS 509: Information Retrieval
INLS 690-270: Data Mining: Methods and Applications


Deborah Barreau Award for Teaching Excellence (2021)
WSDM Best Paper Award (2016)
WSDM Outstanding Reviewer Award (2016)
Dow Distinguished Award for Interdisciplinary Sustainability (2015)


Yue Wang, David Gotz, Ethan M. Basch, Arlene E. Chung. “An Evaluation of Clinical Natural Language Processing Systems to Extract Symptomatic Adverse Events from Patient-Authored Free-Text Narratives.” AMIA 2021 Informatics Summit. (2021)

Jiaming Qu, Jaime Arguello, Yue Wang. “A Deep Analysis of an Explainable Retrieval Model for Precision Medicine Literature Search.” European Conference on Information Retrieval (ECIR). (2021)

Qifei Dong, Yue Wang. “Enhancing Medical Word Sense Inventories Using Word Sense Induction: A Preliminary Study.” The 6th International Workshop on Data Management and Analytics for Medicine and Healthcare, in conjunction with the 46th International Conference on Very Large Data Bases (VLDB). (2020)

Lu He, Changyang He, Yue Wang, Zhaoxian Hu, Kai Zheng, Yunan Chen. “What Do Patients Care About? Mining Fine-grained Patient Concerns from Online Physician Reviews Through Computer-Assisted Multi-level Qualitative Analysis.” American Medical Informatics Association Annual Symposium (AMIA). (2020)

Jiaming Qu, Jaime Arguello, Yue Wang. “Towards Explainable Retrieval Models for Precision Medicine Literature Search.” 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), Xi’an, China. (2020)

Xuedong Li, Yue Wang, Dongwu Wang, Walter Yuan, Dezhong Peng, Qiaozhu Mei. “Improving Rare Disease Classification Using Imperfect Knowledge Graph.” BMC Medical Informatics and Decision Making, 19, Article number: 238. (2019)

Jiatong Li, Kai Zheng, Hua Xu, Qiaozhu Mei, Yue Wang. “The Strength of the Weakest Supervision: Topic Classification Using Class Labels.” Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL). (2019)

Yue Wang, Kai Zheng, Hua Xu, Qiaozhu Mei. “Interactive Medical Word Sense Disambiguation with Informed Learning.” Journal of American Medical Informatics Association (JAMIA). (2018)

Yue Wang, Kai Zheng, Hua Xu, Qiaozhu Mei. “Clinical Word Sense Disambiguation with Interactive Search and Classification.” American Medical Informatics Association (AMIA) 2016 Annual Symposium Proceedings, pages 2062-2071. PMID: 28269966 (2016)

Yue Wang, Dawei Yin, Luo Jie, Pengyuan Wang, Makoto Yamada, Yi Chang, Qiaozhu Mei. “Beyond Ranking: Optimizing Whole-Page Presentation.” Proceedings of the 9th ACM International Conference on Web Search and Data Mining (WSDM’16), pages 103-112. (2016) [Best Paper Award]