I am an Assistant Professor of Sociology at Princeton University where I am also affiliated with the Politics Department, the Office of Population Research, the Princeton Institute for Computational Science and Engineering, and the Center for the Digital Humanities. I develop new quantitative statistical methods for applications across computational social science. I completed my PhD in Government at Harvard in 2015 where I had the good fortune of working with the interdisciplinary group at IQSS. I also earned a master's degree in Statistics from Harvard in 2014.
I've worked extensively on methods for automated text analysis and with Justin Grimmer published an introduction to the field. Molly Roberts, Dustin Tingley and I have developed the Structural Topic Model, an unsupervised topic model geared towards inference in the social sciences. The accompanying software stm is available on CRAN and at structuraltopicmodel.com. It also include a full vignette demonstrating its use.
I've recently been working on Latent Factor Regressions which provide a general framework for modeling dependent data. The framework covers numerous data types including grouped/multilevel, time-series cross-sectional, spatial and network data, all with a single approach. While previous proposals in the literature can take days to estimate a single model, estimation under my framework often takes less than a second. I will release an R package implementing these new methods.