Yingye Zheng, PhD

/content/dam/www/faculty-photos/Z/yingye-zheng/yingye-zheng.jpg
Dr. Yingye Zheng PhD
faculty member

Yingye Zheng, PhD

Professor, Public Health Sciences Division, Fred Hutch

Professor
Public Health Sciences Division, Fred Hutch

Member, Translational Data Science Integrated Research Center (TDS IRC), Fred Hutch

Member
Translational Data Science Integrated Research Center (TDS IRC), Fred Hutch

Fax: 206.667.5977
Mail Stop: B3-B232

Dr. Yingye Zheng is a biostatistician who develops novel statistical tools for medical decision-making related to disease screening, diagnosis, prognosis and outcome prediction. Her work includes evaluating how useful potential biomarkers and disease-risk models will be/are for real patients in the clinic and how to use electronic medical records to evaluate cancer screening techniques. She also studies how to use molecular signals that change over time (called longitudinal biomarkers) to dynamically predict risk and monitor patients’ disease status. Dr. Zheng is an investigator in the Fred Hutch-based Data Management and Coordinating Center of the Early Detection Research Network, or EDRN, a national network that develops, evaluates and validates biomarkers for early detection and risk assessment for cancer. She also is co-principal investigator of the Hutch-based Coordinating Center for the Population-based Research to Optimize the Screening Process II, or PROSPR II, a national consortium that aims to reduce false-positive and false-negative test results in cancer screening.

Other Appointments & Affiliations

Affiliate Professor, Biostatistics, University of Washington School of Public Health and Community Medicine

Affiliate Professor, Biostatistics
University of Washington School of Public Health and Community Medicine

Education

PhD, Biostatistics, University of Washington, 2002

MS, Biostatistics, University of Washington, 1999

MA, Psychology, Washington University in St. Louis, 1997

BS, Psychology, Peking University, 1992

Research Interests

Evaluation of clinical utilities of novel biomarkers and risk models with censored time-to-event outcome

Dynamic risk prediction and disease surveillance with longitudinal biomarkers

Evaluation of cancer screening process (recruitment, screening, diagnosis, and referral for treatment) using electronic medical records from health care systems