Topological Data Analysis has been applied to a number of problems in order to study the geometric and topological structure of point cloud data. In this talk, we discuss their application to the analysis of time series from cyborg-insect and human motion. These tools allow us to identify different type of motion behaviors from the agents, and can help us identify geometric structure of their surroundings. The mathematical framework developed allows us to derive bounds on the sampling of the data space in order to ensure recovery of the correct topological information, and also provide guarantees on the robustness of these quantities to perturbations on the data.
BIO: Dr. Edgar J. Lobaton has been a faculty in the Department of Electrical and Computer Engineering at North Carolina State University (NCSU) since 2011. Dr. Lobaton earned his B.S. in Mathematics and Electrical engineering from Seattle University in 2004. He completed his Ph.D. in Electrical Engineering and Computer Sciences from the University of California, Berkeley in 2009. He was awarded the NSF CAREER Award in 2016, and the 2009 Computer Innovation Fellows post-doctoral fellowshis. His research focuses on the areas of topological data analysis and machine learning with applications to wearable technologies and autonomous systems.
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