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.