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Goldman Sachs Distinguished Lecture – Anna Gilbert
December 1, 2017 @ 9:40 am - 11:30 am
Herman H. Goldstine Collegiate Professor
University of Michigan
December 1, 2017
9:50 am refreshments
10:00 am lecture
The interplay of (sparse) analysis and algorithms
I will discuss the role of sparsity in the theoretical foundations of data science, mathematics, and algorithms. I’ll give two examples from what might be viewed as traditional applied math but examples which have a “data science” twist to them and innovative algorithms or algorithmic insight.
Anna Gilbert received an S.B. degree from the University of Chicago and a Ph.D. from Princeton University, both in mathematics. In 1997, she was a postdoctoral fellow at Yale University and AT&T Labs-Research. From 1998 to 2004, she was a member of technical staff at AT&T Labs-Research in Florham Park, NJ. Since then she has been with the Department of Mathematics at the University of Michigan, where she is now the Herman H. Goldstine Collegiate Professor. She has 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), a National Academy of Sciences Kavli Fellow (2012), and the SIAM Ralph E. Kleinman Prize (2013).
Her research interests include analysis, probability, networking, and algorithms. She is especially interested in randomized algorithms with applications to harmonic analysis, signal and image processing, networking, and massive datasets.