I am a PhD student at Princeton University in Computer Science. At Princeton, I am advised by Ryan P. Adams and Barbara Engelhardt, and I also collaborate with Tamara Broderick at MIT. I am a member of the Laboratory for Intelligent Probabilistic Systems Group and the Biological and Evolutionary Explorations using Hierarchical Integrative Statistical Models Group. Previously, I received an A.B. in Computer Science and Statistics from Harvard University, an M.S. in Statistics from the University of Chicago, and an M.A. in Computer Science from Princeton University. Currently, I am a member of the Women in Machine Learning Board of Directors. My research is generously supported by a Google PhD Fellowship in Machine Learning.
Research interests: I am broadly interested in developing robust and reliable methods for data analysis and understanding their properties. I’m particularly interested in probabilistic inference and uncertainty quantification, with a focus on Bayesian methods under model misspecification and approximate inference.