I am an associate professor in the Ming Hsieh Department of Electrical and Computer Engineering, Computer Science, and Industrial and Systems Engeineering (ISE) at the University of Southern California where I hold an Andrew and Erna Viterbi Early Career Chair. I am also the inaugural director of the USC Center on AI Foundations for Science (AIF4S). Prior to joining USC I spent a year as a postdoc in the AMPLAB at UC Berkeley mentored by Ben Recht and Martin Wainwright. I obtained my Ph.D. in Electrical Engineering from Stanford in 2014 advised by Emmanuel Candes.
My research focuses on developing the mathematical foundations of learning from signals and data spanning optimization, machine learning, signal processing, high dimensional probability/statistics, computational imaging and artificial intelligence. Over the last few years, I've been developing and analyzing algorithms for non-convex optimization with provable guarantees of convergence to generalizable global optima including those arising in deep learning. A particular focus on the application side has been on developing AI for scientific applications in areas such as computational imaging, medical imaging and wireless systems. Here is a copy of my CV.
On the weekends you're most likely to find me cycling on the Pacific coast ranging from Malibu/Santa Monica mountains to Palos Verdes.