Welcome! I study political institutions, causal inference, text analysis and machine learning. My research focuses on understanding how technology shapes democractic political institutions and administrative decision making with a focus on American and European political institutions. I also do research on the political economy of immigration in the United States and religion and politics.

My work in political methodology and statistics lies at the intersection of machine learning and causal inference. Research in this area includes using machine learning algorithms to improve upon classical causal inference techniques, text-as-data, image analysis, scalable missing data imputation and Bayesian causal inference.

I teach or have taught courses on text analysis, applied machine learning, causal inference, statistics, programming and public policy at the University of Georgia, Harvard University, Princeton University and the University of California, Berkeley.

If this sounds interesting, find out more from my CV or my page describing some of my research interests in more detail.

You can also contact via email at: ljasonanastas@gmail.com.