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Research Challenges in Computing – Bei Wang Phillips
August 30, 2024 @ 11:00 am - 12:00 pm
Bei Wang Phillips
Associate Professor
Friday, August 30,
11:00am
3147 MEB
https://utah.zoom.us/j/99963204158?pwd=tEpfDa4bQrzT7echP32lnt3LbY8fyP.1
Meeting ID: 999 6320 4158
Passcode: 595106
Research Challenges in Topological Data Analysis and Visualization
Abstract:
In this talk, I will discuss research challenges in topological data analysis and visualization. I will start with a brief introduction to the field, followed by a discussion of recent advances in topological descriptors and topological deep learning. I will also discuss research activities involving the analysis and visualization of hypergraphs and scientific datasets from climate simulations. I will also describe the intersection between topology and visualization for machine learning interpretability.
Bio:
Dr. Bei Wang Phillips is an Associate Professor in the Kahlert School of Computing and a faculty member in the Scientific Computing and Imaging (SCI) Institute, University of Utah. She obtained her Ph.D. in Computer Science from Duke University. Her research focuses on topological data analysis, data visualization, and computational topology. She works on combining topological, geometric, statistical, data mining, and machine learning techniques with visualization to study large and complex data for information exploration and scientific discovery. Dr. Phillips is a DOE Early Career Research Program (ECRP) awardee in 2020 and an NSF CAREER awardee in 2022. Her research has been supported by multiple awards from NSF, NIH, and DOE.