In person
Palmer Commons, Forum Hall
Remote (In person)
NCRC Building 520, Room 1140
“Topological Data Analysis of Spatial Systems”
Abstract
I will discuss topological data analysis (TDA), which uses ideas from topology to quantify the "shape" of data. I will focus in particular on persistent homology (PH), which one can use to find "holes" of different dimensions in data sets. I will briefly introduce these ideas and then discuss a series of examples of TDA of spatial systems. The examples that I'll discuss include voting data, the locations of polling sites, and the webs of spiders under the influence of various drugs.
Professor, Department of Mathematics, UCLA
Professor, Department of Sociology, UCLA
External Professor, Santa Fe Institute
I am interested in numerous areas of applied mathematics, and I am always looking for new areas to try. Here are a few keywords describing areas in which I have already written research papers or have projects in progress:
Nonlinear Science, Nonlinear Dynamics and Chaos, Nonlinear Waves (including solitary waves, compactions, etc.), Billiard Systems, Quantum Chaos, Granular Media, Nonlinear Optics, Atomic Physics (specifically, Bose-Einstein condensation), Network Science, Social Network Analysis,
Professor