Bio: Rachel Springer is a PhD student at the NYU Center for Data Science where she is co-advised by Dr. Rajesh Ranganath and Dr. Jaume Vives-i-Bastida. Her research focuses on causal inference, probabilistic machine learning, and statistical applications to social science. Before joining NYU, she worked with the Columbia Labor Lab, Monumental Labs, and NASA Deep Space Network, and received a B.A. in Computer Science- Intelligent Systems and a B.A. in Sociology from Columbia University.