Hi. I’m a graduate student in the Kelly Laboratory at Rice University. In terms of research, I’m interested in what new levels of understanding humans can achieve with the access and tools for swimming in the “data deluge,” which is framed as a big problem. In science, often times researchers are collecting or creating data more efficiently than they can process it. More specifically I work in compressive sensing, which aims to dam the deluge by randomly projecting the data, which is assumed to live in some n-dimensional vector space, into an m-dimensional vector space with m<n. This leads to an underdetermined set of equations, but thanks to results on the theory of ill-posed problems, the full n-length vector can be reliably recovered most of the time with high probability if that n-length vector has some intrinsic structure. This is the basic principle of image compression. By taking account of this structure we can take far less measurements than traditionally required, which can lead to a more efficient measurement scheme. To this end, I build and run experiments, both on the optical table and in software on my desktop or on one of the four excellently maintained clusters of the Rice University Research Computing Support Group.
Check this blog for my stuff I’ve figured out or been working on, random and deterministic thoughts, and links to what I’ve been reading. As a true journal, most of the posts are in need of editing that will never happen.