Yejun Wu
Associate Professor
Computer Science and Engineering
Louisiana State University
United States of America
Biography
Yejun Wu is an associate professor in the School of Library and Information Science at the Louisiana State University (LSU). His education background includes a Bachelor of Engineering degree from Jilin University (China), a Master of Science from the Institute of Scientific and Technical Information of China, and a Ph.D. in information studies from the University of Maryland, College Park (UMCP). While at UMCP, he did most of his research at the Laboratory for Computational Linguistics and Information Processing, Institute for Advanced Computer Studies. He is on the adjunct faculty of the Interdepartmental Program in Linguistics at LSU. His work experience includes being an assistant and associate research professor at the Institute of Scientific and Technical Information of China (ISTIC) where he worked on S&T policy analysis and decision support systems, and being in a series of administrative positions at ISTIC (such as deputy director of information analysis & research, director of marketing, and director of administration).
Research Interest
Dr. Wu’s research areas are knowledge organization systems (such as taxonomy, classification, thesaurus, topic maps, and ontology), information retrieval systems (especially cross-language information retrieval and text classification), computational linguistics for text analysis, and open-source information analysis education (including critical thinking).
Publications
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Yejun Wu and Li Yang, 2015. Expanding an oil spill semantic relations taxonomy with a foreign policy semantic relations taxonomy, Proceedings of the 2015 Annual Meeting of the Association of the American Society for Information Science & Technology (ASIS&T), November 6-10, 2015, St. Louis, MO, USA. (to appear)
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Yejun Wu (Ed.), 2016. Oil Spill Impacts: Taxonomic and Ontological Approaches. CRC Press (available at Amazon.com and CRCpress.com).
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Yejun Wu, Amanda Lehman, and David Dunaway, 2015. Evaluations of a large topic map as a knowledge organization tool for supporting self-regulated learning, Knowledge Organization 42(6):386-397.
