Michael obtained his Ph.D. from Stanford University in 2012, after which he spent two years as a postdoc in the Theory of Computation Group at MIT CSAIL, and a year as a Herman Goldstine Postdoctoral Fellow at the IBM T.J. Watson Research Center. He is broadly interested in theoretical computer science, with an emphasis on theoretical foundations of big data analysis. Most of his algorithmic work is in sublinear algorithms, where specific directions include streaming, sketching, sparse recovery and Fourier sampling.