In this research program, I develop methods to identify and estimate causal effects when units interact with each other on networks and across space.
I have worked on identification of causal network effects from observational data in the presence of unmeasured confounding as well as from randomized experiments with interference.
Key words: Interference, Peer effects, Diffusion effects, Homophily
In this research program, I develop methods to improve external validity and generalizability.
I have proposed a formal framework of external validity, developed methods for improving external validity of conjoint analysis, and examined how to select covariates for generalization.
Key words: External validity, Generalization, Cumulative learning
In this research program, I extend machine learning methods, which are originally developed for prediction, to answer causal questions in the social sciences.
I have worked on how to make causal inference with text data, and extended regularized regression to estimate causal interaction in factorial experiments.
Key words: Machine learning, Text analysis, Regularization