Title: The Versatile Forman-Ricci curvature and its Networks Applications
By Emil Saucan, Associate Professor at the Applied Mathematics Department, ORT Braude College
Abstract: We present the adaptations of Forman's discretization of Ricci curvature to the setting of networks and their higher dimensional generalizations and we explore their applications to a variety of real-life applications, such as: brain networks, chemical reactions, financial market crashes, stem cells and cancer research, autism understanding, intelligence of communication and social networks, deep learning, texture understanding, psychology and semantics. We also show how it naturally allows for the understanding of the long-time evolution of networks, their sampling as well as their study through persistent homology.
Location & Time: CSL B02, October 6, 3-4PM
Reception in CSL 154 at 2:30PM.
Bio: Emil Saucan holds a MA degree from the University of Bucharest, and MSc and PhD degrees from the Technion, all of them in pure Mathematics. His research interests have drifted towards more applied fields, mainly to Discrete Differential Geometry and quasi-conformal mappings, and their applications to Complex Networks, Medical Imaging and Sampling Theory. He has been a postdoctoral researcher at the Technion and at the Open University, and had visiting positions at EPFL, MSRI Berkeley, Dalian University of Technology and the Max Planck Institute for Mathematics in the Sciences, Leipzig. He is an Associate Professor at Braude College of Engineering, Karmiel and is currently on a sabbatical in the Department of Computational Medicine & Bioinformatics, at the University of Michigan, Ann Arbor.