Bei Wang Phillips

Assistant Professor, School of Computing; and Faculty Member, SCI Institute, University of Utah

Bei Wang Phillips is an assistant professor at the School of Computing and the Scientific Computing and Imaging (SCI) Institute, University of Utah. From 2011 to 2016, she was a research computer scientist at the SCI Institute.

Bei is primarily interested in data analysis and data visualization. Her research interests include theoretical and algorithmic aspects in computational topology and computational geometry; foundations, techniques, and applications for scientific data analysis and visualization; computational biology and bioinformatics; machine learning; and data mining. She has also worked on projects related to molecular modeling and simulation, as well as robotics.

Some of Bei's recent research activities involve the analysis and visualization of volumetric data, vector field data and high-dimensional data; kernel density estimates; multivariate data analysis involving Jacobi sets, Reeb spaces, and category theory; and stratification learning, as well as active learning.

Bei's research expertise lies in the theoretical, algorithmic, and application aspects of data analysis and data visualization, with a focus on topological techniques. Her vision is to tackle problems involving large and complex forms of data that require rich structural descriptions, by combining topological, geometric, data analysis, and visualization techniques.

Bei's research leverages topological data analysis, which provides a strong theoretical basis for transforming large, complex data into compact, structure-highlighting representations. Topological data analysis captures complex interactions in a system via simplicial complexes, describes features at all scales via persistent homology, is robust with respect to noise, and provides efficient computation. Such a versatile approach connects naturally with and provides infrastructures for data visualization and spurs the rethinking of interactive data exploration to facilitate analytical reasoning.

Bei holds a Ph.D. in Computer Science (2010) and a certificate in Computational Biology and Bioinformatics (2010) from Duke University. She was a visiting researcher at the Institute of Science and Technology Austria in the fall of 2009.


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