E-mail: annacg at umich dot edu

Phone: +1 734 224 8535

My research interests include analysis, probability, discrete mathematics, and algorithms. I am especially interested in randomized algorithms with applications to harmonic analysis, signal and image processing, and massive datasets.


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 the Herman H. Goldstine Collegiate 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).


Latest news

  • Jun Z. Li (Departments of Human Genetics and Computational Medicine and Bioinformatics) and I are the co-directors of the Michigan Center for Single-Cell Genomic Data Analytics. Our research team will connect mathematicians and data scientists with biological researchers to develop, evaluate, and implement a variety of cutting-edge methodologies in sparse data analysis.
  • I will be on sabbatical during the academic year 2017--2018 and have received a Simons Fellowship in Mathematics for 2017.
  • New paper on combinatorial inverse problems: Francis J. Chung, Anna C. Gilbert, Jeremy G. Hoskins, John C. Schotland, Optical tomography on graphs, 2016.

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.