Arthur Spirling is Associate Professor of Politics and Data Science at New York University. He is Director of Graduate Studies at the Center for Data Science (MSDS). He received a bachelor’s and master’s degree from the London School of Economics, and a master’s degree and PhD from the University of Rochester. Spirling’s research centers on quantitative methods for analyzing political behavior, and he is particularly interested in institutional development and the use of text-as-data. His work on these subjects has appeared in outlets such as the American Political Science Review, the American Journal of Political Science and the Journal of the American Statistical Association. Recent projects involve the application of unsupervised and supervised learning to legislative behavior, along with more technical work on the statistical underpinnings of ‘word embeddings’.