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Yi Chen is the Martin Tuchman ’62 Chair and a Professor in Business Data Science in the Martin Tuchman School of Management. She is an affiliated faculty member of the Henry J. and Edna D. Leir Research Institute for Business, Technology, and Society, and also holds a joint appointment in the Computer Science Department at Ying Wu College of Computing Sciences, in New Jersey Institute of Technology (NJIT). She previously held the Henry J. Leir Chair in Healthcare. Prior to joining NJIT, she was an Associate Professor in Arizona State University. She received her Ph.D. degree in Computer Science from the University of Pennsylvania in 2005 and B.S. from Central South University in 1999. She and her research group develop cutting-edge data mining, machine learning and data management techniques for applications in healthcare, business and Web. Some of her current projects include natural language processing on clinic notes and user-contributed content in online health communities, patient risk assessment, user behavior analytics and recommendation systems for user engagement, revenue and user privacy study in online publishing ecosystems. Chen has served in the organization and program committees for prestigious conferences, including SIGMOD, VLDB, ICDE, CIKM and SIGIR, served as an Associate Editor for TKDE, DAPD, PVLDB, INFORMS Journal on Computing, ECRA, and Journal of Healthcare Informatics Research, as well as a general chair for SIGMOD'2012. She served as the Inaugural Director for the Henry J. and Edna D. Leir Research Institute for Business, Technology, and Society, and the Inaugural Director of the PhD program in Business Data Science. Chen is a recipient of a PVLDB Distinguished Associate Editor Award, MTSM Excellence in Research Awards (NJIT), a Peter Chen Big Data Young Researcher Award, Outstanding Faculty Researcher in Computer Science and Engineering (ASU), Google Research Awards, IBM Faculty Awards, an NSF CAREER Award, and a distinguished alumna of the University of Pennsylvania. Her research is funded by National Science Foundation (NSF), the Leir Foundation, National Institutes of Health (NIH), Google, IBM, Science Foundation Arizona, and Department of Defense (DoD).

Computational Advertising: A Study of Online Ad Revenues and User Behaviors
We are developing both analytical and predictive models to study the impact of online Ads to publishers and users, as well as user behaviors.
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Toward Effective Search and Knowledge Discovery in Online Health Forums
We are investigating a patient-centered approach for information extraction, classification, and integration to support effective search and knowledge discovery in healthcare forums.
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XSEEK : an Intelligent Search Engine for Semi-Structured Data
We are developing a search engine for databases. We are identifying a spectrum of problem space for supporting keyword search on structured/semi-structured data, ranging from evaluation framework, generating high-quality results, to helping users analyze results, and developing techniques to address the open challenges. More Information about XSEEK

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Yi Chen

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