I am a PhD candidate at California Institute of Technology (CalTech). My advisor is Babak Hassibi. Generally speaking, I am interested in various problems in signal processing, coding, information theory, discrete optimization, graphical models and inference algorithms. The main focus of my current research is targeting problems in "compressive sensing", including theoretical aspects of sparse signal recovery, novel recovery algorithms and applications of sparse signal processing and low rank matrix recovery/completion to communication systems, control, machine learning and vision. Compressed sensing has a great deal of topics in common with discrete optimization, coding theory, combinatorial geometry and, in the case of our problems, with random graph theory.
Research Interests
Signal Processing, Statistical Inference, LDPC Codes, Communication Systems, Graphical Models, Compressed Sensing and Rank Minimization.
