Anne & Bill Swindells Professor
Professor of Mathematics
In recent years, it has become possible to collect very large amount of data of extremely varied types. Analyzing these data sets is a problem which is now recognized as one of the fundamental intellectual problems facing the scientific and mathematical communities. Topology can be characterized as the study of shape, and most data sets are equipped with a notion of shape, via a metric which captures the notion of similarity of data points. From this observation, one can attempt to adapt topological methods to studying these data. In these talks, we will present a number of methods based on topological methods and ways of thinking, with examples.