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E-mail: annacg at umich dot edu

Phone: +1 734 224 8535

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, and massive datasets.

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 also have a joint appointment in Electrical and Computer Engineering. 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).

C.V.

Latest news

  • In Fall 2016, I will be teaching M571 (Numerical Linear Algebra). M571 focuses on algorithms for linear algebra problems (solving linear systems, eigenvalue problems, and least squares problems) which are at the foundation of much of scientific computing, data science, machine learning, digital signal and image processing, network analysis, etc.
  • I will also teaching M556 (Applied Functional Analysis). M556 covers topics in functional analysis that are used in the analysis of differential equations, signal processing, and theoretical computer science. We will cover the following topics: metric and normed linear spaces, Banach spaces, Hilbert space, spectral theory of compact operators, distributions and Fourier transforms, Sobolev spaces, dual spaces, convex analysis, and applications.
Teaching

Research Projects

My research sits at the boundaries of several disciplines, including mathematics, computer science, and statistics. I have worked on or am working in three main areas: (i) computational harmonic analysis or sparse approximation and sparse signal recovery, (ii) algorithms (especially sublinear or streaming algorithms), and (iii) applications of sparse analysis in signal processing, sensor networks, network traffic analysis, inverse problems, and high throughput biological screens. This interplay of mathematics and computing is crucial in identifying and solving fundamental problems in science and my vision for my research is to make lasting contributions to both mathematics and science through this interdisciplinary work.