معرفی
Bei Wang Phillips is an Associate Professor in the School of Computing and a faculty member at the Scientific Computing and Imaging (SCI) Institute at the University of Utah. She holds a Ph.D. in Computer Science from Duke University and an undergraduate degree from the University of Bridgeport. Her research focuses on Topological Data Analysis (TDA), data visualization, computational topology, and machine learning, with applications in scientific data exploration and analysis. She has received prestigious awards including the NSF CAREER Award (2022) and the PECASE Award (2025). Her work spans projects funded by NSF, NIH, and DOE, including multiparameter TDA and topology-aware data compression. She advises numerous students and collaborates on interdisciplinary initiatives in astrophysics, climate science, and AI fairness.
Education:
- Ph.D. in Computer Science, Duke University (2010)
- B.S. in Computer Science and Mathematics, University of Bridgeport (2003)
Research Interests:
- Topological techniques for large-scale data analysis
- Integration of topological, geometric, and machine learning methods
- Applications in visualization, bioinformatics, and network analysis
Key Projects:
- NSF-funded TDA research (DMS-2301361, OAC-2313124)
- DOE project on topology-preserving data compression
- Collaborations with NASA, Argonne National Lab, and Carnegie Institution of Washington
Awards:
- Presidential Early Career Award for Scientists and Engineers (2025)
- NSF CAREER Award (2022)
- DOE Early Career Research Program (2020)
Advising and Grants:
- Mentored over 30 students and postdocs
- Recipient of multiple NSF and DOE grants totaling millions
