Linying Zhang

Linying Zhang, PhD, is an Assistant Professor of Biostatistics, Statistics and Data Science, and Medicine at Washington University School of Medicine in St. Louis. She holds affiliations with the Institute for Informatics, Data Science, and Biostatistics (I2DB), the Roy and Diana Vagelos Division of Biology & Biomedical Sciences (DBBS), and the Center for Biostatistics and Data Science (CBDS). Her research focuses on causal inference and machine learning applied to large-scale healthcare databases, particularly addressing treatment disparities and developing federated causal machine learning frameworks.

• Education:
  • PhD in Biomedical Informatics, Columbia University
  • MS in Computational Biology, Harvard University
  • BA in Biochemistry and Molecular Biology, Boston University

Her research interests include improving healthcare equity through algorithmic fairness, personalized treatment planning via heterogeneous treatment effect estimation, and federated learning across multiple databases. She mentors PhD/MSTP students and postdoctoral fellows.

Recent publications explore topics like semaglutide-associated optic neuropathy risks, causal fairness in treatment allocation, and machine learning for fall risk prediction in older adults. Her work has been recognized in journals such as JAMA Ophthalmology and the Journal of Biomedical Informatics.

She leads efforts in labs focused on biomedical informatics and data science, emphasizing reproducible research and interdisciplinary collaboration.