The ACM Algorithms and Computation Theory group has awarded this year's Knuth Prize to Ravi Kannan of Microsoft Research Labs India for
"developing influential algorithmic techniques aimed at solving long-standing computational problems."
Much of the work that is cited as the reason for awarding the prize might seem very abstract but there are also some very practical areas of research.
The main paper that is cited presents an algorithm that runs in polynomial time for estimating the volume of a convex body in n dimensional space. It makes use of a random walk on the convex body generated by a type of Markov chain. A large part of Kannan's work is about random algorithms using Markov chains.
Another more practical area of research is the application of mostly random algorithms to big data and sampling. For example a fast Monte Carlo algorithm that produces an approximate matrix multiplication has all sorts of practical applications. Clustering algorithms also figure in the research, as do lattice algorithms.
Overall the focus of the research is on algorithms and as such Kannan is a good choice for this prize which is associated with the father of the analysis of algorithms, Donald Knuth.
ACM's announcement of award
Ravi Kannan's home page where you will find PDFs of all of his papers.