Machine intelligence for processing big data sets is big business. A statistical mathematician's point of view has led to (1) effective large-scale principal component analysis and singular value decomposition, and (2) some theoretical foundations for convolutional networks (convolutional networks underpin the recent revolution in artificial intelligence).
Prior to joining Facebook Artifical Intelligence Research, Dr. Tygert held positions on the faculty at NYU’s Courant Institute, UCLA, and Yale, following undergraduate, graduate, and postdoctoral studies at Princeton and Yale. Research focuses have included fast spherical harmonic transforms, randomized algorithms for linear algebra, and complements to chi-square tests. Recent honors include the 2010 William O. Baker Award from the U.S. National Academy of Sciences and a 2012 DARPA Young Faculty Award.