Topological Data Analysis of Dynamic Networks
Our research focuses on constructing new nonparametric methods for anomaly detection on dynamic networks using the emerging tools of topological data analysis. In particular, we describe shapes of complex networks via analysis of simplicial complexes and then track fluctuations of the resulting topological signatures over time. We validate our methods in applications to networks from social sciences, telecommunication and blockchain.
UoManitoba - PSU - UTDallas
Ignacio Segovia-Dominguez
Visiting Scientist / Postdoctoral Research Associate
My research interests include topological and geometric methods in statistics and machine learning, analysis of complex dynamic networks, evolutionary computation, and computational statistics.