The Shape of Data

In recent years there has been a lot of attention given to "Big Data".  In fact, many of the problems that need to be addressed relate not to the "Big", but rather in the inherent complexity of much of the important data that is being produced.  What this means is that there is a need for an organizing principle for data analysis.  One such organizing principle uses methods from Topology, the mathematical discipline which concerns itself with the study of shape, or rather the higher dimensional generalization of shape.  The methods give rise to new methods of modeling data, as well as feature creation and invariants of the shape of the data which are readily interpretable.  We will discuss these ideas, with numerous examples from various areas within the sciences and industry.

Speaker: Gunnar Carlsson, Ayasdi Inc.