Zach Butzin-Dozier, Ph.D.


Zach is a postdoctoral scholar in the Division of Biostatistics at the UC Berkeley School of Public Health working under Professors Alan Hubbard, Jack Colford, and Mark van der Laan. His work applies Targeted Machine Learning methodology to COVID-19 data, explores methods of synthetic data creation to improve data sharing and collaboration, and evaluates the relationships between maternal milk composition and child growth and development. In addition, his research evaluates drivers of WASH intervention effectiveness and poor development for children in Bangladesh. He received his Ph.D. in Epidemiology and MPH in Epidemiology and Biostatistics from UC Berkeley.

Research interests: 
Causal inference, targeted machine learning, synthetic data, adaptive trial design, optimal treatment regimes, child development, stress neurobiology, and antimicrobial resistance