University of Edinburgh
Peter Richtárik is an Associate Professor in the School of Mathematics, University of Edinburgh. He obtained his PhD from Cornell University in 2007, spent two years as a postdoctoral fellow at Universite Catholique de Louvain. Recently, he has been a visiting researcher at the Simons Institute at UC Berkeley and a Faculty Fellow at the Alan Turing Institute – the UK national research centre for data science. Prof Richtárik has made fundamental contributions to “big data optimization”, which is an emerging field at the intersection of mathematical optimization, convex analysis, probability theory, computer science, machine learning and high performance computing. He is the recipient of an EPSRC Fellowship in the Mathematical Sciences. Peter developed the theory of randomized coordinate descent and stochastic gradient methods of various flavours for convex optimization in very high dimensions. These algorithms have substantially better complexity bounds than previous deterministic methods, and have state-of-the-art practical performance for key statistical learning tasks involving large data. Prof Richtárik is the recipient of the 2016 SIAM SIGEST Paper Award and a 2016 EUSA Best Research or Dissertation Supervisor Award.