Skip to main content

Speaker Profile

Peter Richtárik

KAUST

Biography

Peter Richtarik is an Associate Professor of Computer Science and Mathematics at KAUST and an Associate Professor of Mathematics at the University of Edinburgh. He is an EPSRC Fellow in Mathematical Sciences, Fellow of the Alan Turing Institute, and is affiliated with the Visual Computing Center and the Extreme Computing Research Center at KAUST. Dr. Richtarik received his PhD from Cornell University in 2007, and then worked as a Postdoctoral Fellow in Louvain, Belgium, before joining Edinburgh in 2009, and KAUST in 2017. Dr. Richtarik's research interests lie at the intersection of mathematics, computer science, machine learning, optimization, numerical linear algebra, high performance computing and applied probability. Through his recent work on randomized decomposition algorithms (such as randomized coordinate descent methods, stochastic gradient descent methods and their numerous extensions, improvements and variants), he has contributed to the foundations of the emerging field of big data optimization, randomized numerical linear algebra, and stochastic methods for empirical risk minimization. Several of his papers attracted international awards, including the SIAM SIGEST Best Paper Award and the IMA Leslie Fox Prize (2nd prize, three times). He is the founder and organizer of the Optimization and Big Data workshop series.

Website: https://www.kaust.edu.sa/en/study/faculty/peter-richtarik

All sessions by Peter Richtárik

  • MondayFebruary 5
1:45 PM

Richtárik (KAUST): Stochastic Reformulations of Linear and Convex Feasibility Problems: Algorithms and Convergence Theory