|Affiliation:||University of Michigan|
|E-mail:||annacg at umich dot edu|
|Work Cell Phone:||734.224.8535|
East Hall 4844
Department of Mathematics
The University of Michigan
2074 East Hall
530 Church St.
Ann Arbor, MI 48109-1043
|Biography:||I received an S.B. degree from the University of Chicago and a Ph.D. from Princeton University, both in mathematics. In 1997, I was a postdoctoral fellow at Yale University and AT&T Labs-Research. From 1998 to 2004, I was a member of technical staff at AT&T Labs-Research in Florham Park, NJ. Since then I have been with the Department of Mathematics at the University of Michigan, where I am now a Professor. I have received several awards, including a Sloan Research Fellowship (2006), an NSF CAREER award (2006), the National Academy of Sciences Award for Initiatives in Research (2008), the Association of Computing Machinery (ACM) Douglas Engelbart Best Paper award (2008), the EURASIP Signal Processing Best Paper award (2010), and the SIAM Ralph E. Kleinman Prize (2013). My research interests include analysis, probability, networking, and algorithms. I am especially interested in randomized algorithms with applications to harmonic analysis, signal and image processing, networking, and massive datasets.|
We will be hosting SPARC 2013: Coding, Complexity, and Sparsity workshop August 5-7, 2013. The aim of the workshop is to develop a general computational theory of sparse approximation, streaming algorithms, and compressive sensing (as well as related areas such as group testing) and its relationship to coding theory and complexity theory. This goal can be achieved only by bringing together researchers from a variety of areas. We will have several tutorial lectures that will be directed to graduate students and postdocs. Please see SPARC 2013 for more information and registration.
In Fall 2013, I will be teaching M556 (Applied Functional Analysis). This is an introduction to methods of applied functional analysis. Students are expected to master both the proofs and applications of major results. The prerequisites include linear algebra, undergraduate analysis, advanced calculus and complex variables. This course is a core course for the Applied and Interdisciplinary Mathematics (AIM) graduate program. Topics will include Fourier analysis, distributions, Hilbert spaces, Banach spaces, fixed point theorems, etc.
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Last Modified: 10 May 2013