Razieh Nabi

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My overarching goal in research is developing methods that support informed decisions and interventions in settings that require precision and quantified uncertainty, even when available data are imperfect. This entails exploiting tools from causal inference, statistics, and machine learning. Despite the fascinating methodological advances in the field of causal inference over the past few decades, there still remain a plethora of open problems and exciting challenges in this research area. In my research, I pursue multiple directions to continue to provide solutions to open problems and bridge the gap between theory and scientific applications in healthcare, public policy, and social science.

Here is a list of my publications, divided by subject area. (* indicates equal contribution)
See my Google Scholar for a complete list of publications.


Causal Effect Identification and Estimation



Missing Data



Algorithmic Fairness



Precision Medicine



Interference and Dependent Data



Interpretable ML

PhD Thesis