Eric Price is a fourth-year Ph.D. student at MIT researching theoretical aspects of sparse recovery and compressive sensing. He received his bachelor’s degree from MIT in 2009. He is a co-author of several papers, published in conferences such as STOC, FOCS and SODA. One of his algorithms, which Technology Review named one of the top-ten emerging technologies of 2012, computes the discrete Fourier transform faster than the well-known FFT algorithm on sparse data. Another result shows how compressive sensing can significantly benefit from adaptively chosen measurements. A recipient of an NSF graduate research fellowship, he has won gold medals at the International Olympiad in Informatics, International Mathematical Olympiad and ACM International Collegiate Programming Contest.

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Mathematics & Physical Sciences

The Mathematics and Physical Sciences division supports research aimed at advancing our understanding of fundamental questions in mathematics, physics and computer science. Through grants and collaborations, the division brings together researchers to pursue ambitious ideas, develop new approaches and foster scientific exchange.

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