Zach Dozier is a CTML affiliate and an Assistant Professor at Stanford University in the Department of Pediatrics, Division of Clinical Informatics, with a joint appointment in the Department of Medicine, Division of Computational Medicine. His research applies machine learning and artificial intelligence for causal inference via electronic health record data. He draws from large-scale databases, such as the UC Health Data Warehouse, Epic Cosmos, PEDSnet, and the National Clinical Cohort Collaborative, to answer pressing questions in pediatric and infectious disease medicine. His research evaluates vaccine effectiveness, drug repurposing, and the long-term sequelae of viral infection, including Long COVID. He aims to bridge rigorous biostatistical methodology with clinically meaningful research questions. He received his PhD in Epidemiology and MPH from UC Berkeley, and he is an NIAID K01 recipient.
Contact
Job title:
Assistant Professor
Department:
Department of Pediatrics, Division of Clinical Informatics
Department of Medicine, Division of Computational Medicine at Stanford University
Bio/CV:
Research interests:
Causal inference, pediatrics, health informatics, electronic health records, epidemiology
Role:
