PhD, EECS Dept., MIT.
Stochastic Systems Group (SSG),
Laboratory for Information and Decision Systems (LIDS).
I completed the PhD program in 2008 and am
now a director-funded postdoctoral fellow working with Michael Chertkov
at Los Alamos National Laboratory, Center for Nonlinear Studies and Theoretical
Division T-4. Please see my current CNLS webpage
for recent publications.
I attended Appalachian State University for two years before
transferring to MIT, where I graduated S.B. Physics, 1995. During the
next five years, I was a member of technical
staff with Alphatech Inc., where I helped develop algorithms for
multi-resolution signal and image processing, data
fusion and multi-target tracking. In 2000, I entered the EECS
graduate program at MIT under the direction of Alan Willsky, where I
earned the S.M., 2003, and am currently working to
complete the PhD program.
My research has focused on the use of information theory and
convex optimization to provide principled, tractable approximation
methods for solving large-scale inference and estimation problems
involving graphical models, also known as Markov random fields
(MRFs). In particular, Gaussian MRFs (commonly used in image
processing) have played a central role in these investigations.
Here are summaries of several novel methods that I introduced: