We are studying Topological Data Analysis with a focus on methods (approximate, parallel and distributed) to compute Persistent Homology (PH) on large and high-dimensional data sets. Our current studies focus on (i) partitioning coupled with parallel and distributed computing to expand the computation of PH for big data in moderate dimensions (<4); (ii) approximate methods to compute PH on higher dimensional data sets; and (iii) the computation of PH on streaming data.

Before applying for this opportunity you need to submit your online profile. Click the button below to continue.