I am a Postdoctoral Associate in the Statistics Department at Stanford University. I work with David Donoho, and I am supported by a NSF VIGRE grant.

I received my Ph.D. in Electrical Engineering from University of California, Berkeley in 2011. My advisor was Michael Gastpar. In the summer of 2011, I was a postdoctoral researcher at EPFL, Switzerland; in the spring of 2009, I was a visiting scholar at the Technical University of Delft, The Netherlands; and in the summer of 2008, I was a research intern at Microsoft Research, Redmond, where I worked with Jie Liu in the Networked Embedded Computing Group. I received my M.S. in Electrical Engineering from UC Berkeley in 2007, and I received my BS in Electrical and Computer Engineering from Cornell University in 2005.
My research interests are in signal processing, statistics, and information theory, with applications in compressed sensing, massive data storage and retrieval, neuroscience, and machine learning. My Ph.D. dissertation used tools from information theory to provided a sharp characterization of the problem of sparsity pattern recovery in compressed sensing.
Publications (Updated January 2013)
  • STATS 110 - Statistical Methods in Engineering and the Physical Sciences, Autumn, 2011 and 2012.
  • STATS 60 - Introduction to Statistical Methods: Precalculus, Spring, 2012.