She received her Ph.D. in computer science from the University of Chicago in 2006. Her research interests are mostly centered around theoretical analysis of randomized and approximation algorithms, often with emphasis on the Markov chain Monte Carlo technique. She has also worked on graph modeling problems that intersect the areas of machine learning and networking. Her publications have appeared in the SIAM Journal of Computing (SICOMP), Random Structures and Algorithms (RSA), ACM-SIAM Symposium on Discrete Algorithms (SODA), International Conference on Machine Learning (ICML), and others. Her teaching interests include courses with significant algorithmic and/or theoretical content, and the introductory sequence.