WEB 4608
Phone: (801) 585-0968
Fax: (801) 585-6513
Dr. Bei Wang Phillips is an Associate Professor in the School of Computing, an Adjunct Associate Professor in the Department of Mathematics, and a faculty member of the Scientific Computing and Imaging (SCI) Institute at the University of Utah. She received her Ph.D. in Computer Science from Duke University. Her research centers on topological data analysis, data visualization, and computational topology, with a focus on integrating topological, geometric, statistical, data mining, and machine learning methods with visualization to enable information exploration and scientific discovery in large and complex datasets. Her work has been supported by multiple awards from the NSF, NIH, and DOE. Dr. Phillips was a recipient of the DOE Early Career Research Program (ECRP) award in 2020, the NSF CAREER award in 2022, and the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2024.
Dr. Bei Wang Phillips’ research spans the theoretical foundations, algorithmic development, and practical applications of data analysis and visualization, with a central focus on topological techniques. Her work leverages topological data analysis (TDA) to transform large, complex datasets into compact representations that reveal their underlying structure. These structure-aware representations serve as powerful infrastructures for data visualization and motivate new paradigms for interactive data exploration that enhance analytical reasoning. Drawing on ideas from topology, geometry, and machine learning, her current research investigates a broad range of data modalities—including vector fields, high-dimensional point clouds, networks, and multivariate ensembles—while also advancing visualization techniques for improving the interpretability of machine learning models.
Dr. Wang’s research interests span both data analysis and data visualization, including: