Bi-Co Mathematics Colloquium with Dr. Robyn Brooks
Title: "Finding the Shape of Data: How to use Topology to Uncover Patterns in Science"
Abstract: The fundamental hypothesis of Topological Data Analysis (TDA) is that data come as samples taken from an underlying shape, and unveiling that shape is important for understanding the studied phenomenon. In particular, Persistent Homology is a tool of TDA which can be used to determine relevant patterns, dynamics, and topological features of a sample of data points. This tool has a wide range of applications in analyzing data associated to neuroscience, biology, physics, social science, and various other fields. In this talk, I will introduce the persistent homology pipeline, the process in which we associate topological shape to data and obtain interpretable topological summaries for analysis. I will then present some of the (awesomely cool) research projects from my undergraduate research lab in the theory and applications TDA. Finally, throughout the talk, I will speak a bit about my own path in mathematics, how I found community in other mathematicians, and talk a bit about the work that I do in the mathematics community outside of my math research.
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