About

Ying Ding is a Professor in the Department of Biostatistics and Health Data Science at the University of Pittsburgh, where she also serves as Associate Dean for Graduate Academic Affairs in the School of Public Health. Her research develops statistical methodology for complex survival and high-dimensional data, with a sustained focus on precision medicine — from the targeted development of treatments to the estimation of individualized treatment effects.

She earned her Ph.D. in Biostatistics from the University of Michigan in 2010, following a B.S. in Mathematics from Nanjing University and an M.A. in Mathematics from Indiana University Bloomington. Before joining the University of Pittsburgh faculty in 2013, she spent several years as a research scientist at Eli Lilly and Company, an experience that continues to shape her interest in methods that answer real questions in drug development and clinical research.

Dr. Ding's methodological work spans semiparametric theory for interval-censored and bivariate time-to-event data, confident inference for subgroups in randomized trials, and statistical and deep-learning methods for genetic and multi-omics data. This work is developed in close partnership with collaborators studying age-related macular degeneration, Alzheimer's disease and related psychosis, schizophrenia, and pediatric pulmonary disease. A dedicated teacher and mentor, she has advised a generation of doctoral students, and was elected a Fellow of the American Statistical Association in 2025.

Education

Appointments

Selected honors & awards

• 2026Statistician of the Year, American Statistical Association, Pittsburgh Chapter
• 2025Elected Fellow, American Statistical Association
• 2023Outstanding Service Award, ASA Lifetime Data Science Section
• 2022Ascending Star Award, Health Sciences, University of Pittsburgh
• 2021James L. Craig Excellence in Education Award, University of Pittsburgh
• 2010ENAR Distinguished Student Paper Award