Speaker: Dev Sinha, University of Oregon and MIT

Abstract: As its name implies, Topological Data Analysis (TDA) applies the mathematics of shape and deformation to study data. In particular, robustness under deformation can address issues of noise and error, while combinatorial invariants of shape can be used to understand structure in data sets, large and small, especially in high dimensions.
In this talk we share applications of TDA to medicine, psychology, materials science and neuroscience, which have been published in high-quality science journals. We develop only the background needed for the applications, eschewing formalism and assuming no prior knowledge of topology or any of the fields of application.