Research Areas
Please see Papers for the full list of publications and selected working papers.

1. Causal Inference with Network and Spatial Data

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

Selected Papers:

2. External validity, Generalization, and Meta-Analysis

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

Selected Papers:

3. Machine Learning for the Social Sciences and Causal Inference

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

Selected Papers: