She is an Intel Early Career Faculty Fellow, a 3M Non-tenured Faculty Awardee, an ARO Young Investigator, and an AFOSR Young Investigator. She received her PhD from the University of Wisconsin, Madison, MS from the University of California in Los Angeles, and BS from Rice University, all in Electrical and Computer Engineering. She received the Outstanding MS Degree of the year award from the UCLA EE Department, and the Best Dissertation award from the University of Wisconsin ECE Department. Her main research focus is on modeling with big, messy data — highly incomplete or corrupted data, uncalibrated data, and highly heterogeneous data — and its applications in networks, environmental monitoring, and computer vision. Her expertise is broadly in statistical signal processing, matrix factorization, and optimization.