Linying Zhang, PhD, is Assistant Professor of Biostatistics in the Institute for Informatics, Data Science, and Biostatistics (I2DB) at Washington University School of Medicine in St. Louis. Dr. Zhang specializes in causal inference and machine learning for generating reliable real-world evidence from large-scale healthcare databases, such as electronic health records (EHRs) and administrative claims. Her recent research has focused on addressing confounding bias in observational studies, and explaining root causes of treatment disparities from a causal perspective. Her research goals include 1) developing federated causal machine learning for treatment effect estimation across multiple databases without sharing patient-level data, 2) developing heterogeneous and individualized treatment effect estimation algorithms for personalized treatment planning, and 3) improving the equity of health care through machine learning. She is open to mentor undergraduate and graduate students, and post-doctoral fellows. Dr. Zhang has a PhD in Biomedical Informatics from Columbia University, MS in Computational Biology from Harvard University, and BA in Biochemistry and Molecular Biology from Boston University.

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