His father was a professor at Hunter College for decades, and his wife received her MPH from CUNY. Zach received his PhD in statistics from Columbia University advised by David Madigan, was a postdoc at the Harvard School of Public Health supervised by Jamie Robins and Miguel Hernan, and worked at IBM Research in the Department of Healthcare and Life Sciences.
PhD in Statistics and Probability from Columbia University
BA in Mathematics from Stanford University
Zach's research interests center on the theory and application of causal inference methods to estimate time-varying treatment effects using healthcare data. He hopes to contribute to public health by helping to rigorously assess what works and when. He has a particular interest in critical care applications, but is eager to apply causal inference methodology wherever it is useful.