Topology and the Big Data Problem
There is a lot of discussion around "Big Data". Although the size is a problem, complexity, suitably defined, is often a bigger hurdle in the process of extracting knowledge from the data. Topology, the mathematical notion of shape, can act as a very useful organizing principle for many kinds of complex data. In this talk, we will discuss some topological approaches to understanding data, with numerous examples.
Gunnar Carlsson has been working in the area of algebraic topology since he completed his Ph.D. at Stanford in 1976. He has held positions at University of Chicago, University of California, San Diego, Princeton University, and since 1991 at Stanford University. He has been an invited speaker at the International Congress of Mathematicians in Berkeley, and held an Alfred P. Sloan Fellowship. Around the year 2000, he began working on applications of topology to the understanding of complex data sets. He led a multi-university DARPA initiative on this subject, and is also a founder of Ayasdi, Inc., which is commercializing that research.