Speaker: Chao Chen
Abstract: We are facing unprecedented challenges from modern data such as vast volume, high dimensionality, and complex intrinsic structures. To address these issues, we need scalable and robust methods to extract concise, intuitive and discriminative global information from data. Topology data analysis (TDA) is a new area focusing on the extraction and usage of topological structures of data with strong theoretical guarantee. In this talk, I will introduce the main theoretical tools in TDA and their applications. I will also present my recent work of combining the topological view with probabilistic graphical models in machine learning.
Bio: Dr. Chao Chen is an Assistant Professor in City University of New York. His interdisciplinary research lies in between computational topology, machine learning, and biomedical image analysis. His research has been published in top venues in all these domains. For more information, please visit his website.