
Award Number and Duration 
DOE DESC0023157 
PI and Point of Contact 
Bei Wang Phillips (PI, University of Utah) 
Collaborators 
Tom Peterka (Lead PI) 
Overview 
This project investigates how to accurately and reliably visualize complex data consisting of multiple nonuniform domains and/or data types. Much of the problem stems from having no uniform representation of disparate datasets.
To analyze such multimodal data, users face many choices in converting one modality to another; confounding processing and visualization, even for experts. Recent work in alternative data models and representations that are continuous, highorder (nonlinear), and can be queried anywhere (i.e., implicit), suggests that such models can potentially represent multiple data sources in a consistent way. 
Publications and Manuscripts 
Papers marked with * use alphabetic ordering of authors. 
Year 2 (2023  2024)  
Position: Topological Deep Learning is the New Frontier for Relational Learning.
Theodore Papamarkou, Tolga Birdal, Michael Bronstein, Gunnar Carlsson, Justin Curry, Yue Gao, Mustafa Hajij, Roland Kwitt, Pietro Lio, Paolo Di Lorenzo, Vasileios Maroulas, Nina Miolane, Farzana Nasrin, Karthikeyan Natesan Ramamurthy, Bastian Rieck, Simone Scardapane, Michael T. Schaub, Petar Velickovic, Bei Wang, Yusu Wang, GuoWei Wei, Ghada Zamzmi. Proceedings of the 41st International Conference on Machine Learning (ICML), 2024. arXiv:2402.08871  
MeasureTheoretic Reeb Graphs and Reeb Spaces.
Qingsong Wang, Guanquan Ma, Raghavendra Sridharamurthy, Bei Wang. International Symposium on Computational Geometry (SOCG), 2024. arXiv:2401.06748.  
Visualizing Activation Spaces of Morse Complex Generation.
Syed Fahim Ahmed, Jixian Li, Mingzhe Li, Bei Wang. Manuscript in preparation, 2024.  
Critical Point Extraction from Multivariate Functional Approximation.
Guanqun Ma, David Lenz, Thomas Peterka, Hanqi Guo, Bei Wang. Manuscript, 2024.  
Year 1 (2022  2023)  
Interactive Visualization of TimeVarying Flow Fields Using Particle Tracing Neural Networks. Mengjiao Han, Sudhanshu Sane, Jixian Li, Shubham Gupta, Bei Wang, Steve Petruzza, Chris R. Johnson. IEEE Pacific Visualization Symposium (PacificVis), 2024. Supplementary Material.  
TopoSZ: Preserving Topology in ErrorBounded Lossy Compression.
Lin Yan, Xin Liang, Hanqi Guo, Bei Wang. IEEE Visualization Conference (IEEE VIS), 2023. IEEE Transactions on Visualization and Computer Graphics (TVCG), 30, pages 13021312, 2024. Supplementary Material. DOI:10.1109/TVCG.2023.3326920 arXiv:2304.11768. 
Presentations, Educational Development and Broader Impacts 
Year 2 (2023  2024) 

Year 1 (2022  2023) 

Students 
Guanqun Ma (Ph.D., Summer 2023  present) Kahlert School of Computing and SCI Institute University of Utah Syed Fahim Ahmed (Ph.D., Spring 2023  present) Kahlert School of Computing and SCI Institute University of Utah Weiran (Nancy) Lyu (Ph.D., Fall 2022  present) Kahlert School of Computing and SCI Institute University of Utah 
Acknowledgement 
This material is based upon work supported or partially supported by the United States Department of Energy (DOE) under Grant No. DESC0023157. 