My research interests are focused on topological methods in statistics and machine learning. Topological data analysis refers to the analysis of data shape. My research spans from encoding of data into filtered simplicial complexes (topological representation), approximations of filtered simplicial complexes (sparsification), validation measures of unsupervised persistent homology, data benchmarks, efficient vector representations of persistent homology for supervised machine learning and applications of topological methods in biology and geophysics.