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Qing Zeng Qing Zeng
Professor of Clinical Research and Leadership

Office Phone: N/A
Email: Email
Department: Clinical Research and Leadership

Education

  • B.S., Beijing Polytechnic University, 1993
  • M.S., University of Hawaii, 1995
  • MPhil, Columbia University, 1997
  • PHD, Columbia University, 1999

Biography

With 20 years of experience in informatics, Dr. Zeng has special expertise in text mining, consumer health informatics, and semantic integration of data sources. She has published over 80 peer-reviewed articles, as well as served as the PI and Co-PI on a number of VA HSR&D, NIH and DOD funded research projects. Dr. Zeng’s research vision is to leverage information for healthcare research and delivery. Her main research areas are NLP and consumer health informatics. Several of her papers have been selected by the International Medical Informatics Association’s Yearbook and one paper won the Distinguished Paper Award in the 2011 American Medical Informatics Association’s Joint Summit. In 2014, her “HeartsLikeMine” project won first-place award in the “Ideas That Work” contest in the iHealth conference sponsored by the American Medical Informatics Association and Academy Health. Prior to coming to GW, Dr. Zeng was a Professor at the University of Utah and Associate Professor at Harvard Medical School, where she developed an NLP tool (HITEx) for two large consortium projects (i2b2 and SPIN). HITEx was the first open-source, comprehensive clinical NLP system in the nation. In addition to her work at GW, Dr. Zeng is currently the Associate Director of the Center for Health and Aging at the Washington DC VA Medical Center. At the VA, she has organized a VA-wide collaboration to develop interoperability standards for the broader clinical NLP community. The Open Access Collaborative (OAC) Consumer Health Vocabulary (CHV) produced by her team is the first and only consumer health vocabulary that has been incorporated into the Unified Medical Language System. She has also developed a number of novel informatics methods (e.g. automated illustration of instruction and social media analysis) to improve patient-centered care.

Programs

  • Medical Informatics

Industry Relationships and Collaborations

This faculty member (or a member of their immediate family) has reported a financial interest with the health care related companies listed below. These relations have been reported to the University and, when appropriate, management plans are in place to address potential conflicts.

  • None