Bei Wang Phillips |
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Bei Wang Phillips Publish Under: Bei Wang Associate Professor, Kahlert School of Computing Adjunct Associate Professor, Department of Mathematics Faculty member, Scientific Computing and Imaging (SCI) Institute University of Utah Warnock Engineering Building (WEB) Room 4608 72 South Central Campus Drive Salt Lake City, Utah 84112 Email: beiwang AT sci.utah.edu Research keywords: topological data analysis, data visualization, computational topology, data mining, and machine learning. CV: (last update February 17, 2024) Web page last update: November 4, 2024. |
Short Biography
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Professional Experience Education |
Best Paper Awards
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Student Awards
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Research Interests
I am interested in the analysis and visualization of large and complex data. |
Current Projects |
2023 - 2026 NSF DMS-2301361 Multiparameter Topological Data Analysis. Project Website |
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2023 - 2026 NSF OAC-2313124 Topology-Aware Data Compression for Scientific Analysis and Visualization. Project Website |
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2022 - 2027 NSF IIS-2145499 CAREER: A Measure Theoretic Framework for Topology-Based Visualization. Project Website. |
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2022 - 2026 NSF IIS-2205418 SCH: Geometry and Topology for Interpretable and Reliable Deep Learning in Medical Imaging Project Website. |
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2022 - 2025 DOE DE-SC0023157 Implicit Continuous Representations for Visualization of Complex Data. Utah Project Website. |
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2021 - 2024 NSF DMS-2134223 Advancing Theoretical Minimax Deep Learning: Optimization, Resilience, and Interpretability. Project Website. |
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2020 - 2025 DOE DE-SC0021015 Topology-Preserving Data Sketching for Scientific Visualization. Project Website. |
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2021 - 2024 Utah Board of Higher Education Deep Technology Initiative Bringing Fairness in AI to the Forefront of Education. Project Website. |
Past Projects |
2019 - 2022 NSF IIS-1910733 Visualizing Robust Features in Vector and Tensor Fields. Project Website. |
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2017 - 2020 NSF DBI-1661375 ABI Innovation: A Scalable Framework for Visual Exploration and Hypotheses Extraction of Phenomics Data using Topological Analytics. Utah Project Website. Collaborative Project Website. |
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2015 - 2019 NSF IIS-1513616 Topological Data Analysis for Large Network Visualization. Project Web Site. |
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2016 - 2019 NIH 1R01EB022876 Beyond Diagnostic Classification of Autism. Project Website. |
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2016 - 2017 NRAO-NSF Pilot Grant Feature Extraction & Visualization of ALMA Data Cubes through Topological Data Analysis. Project Web Site. |
Students
I am looking for talented undergraduate and graduate students who are interested in data analysis and data visualization. Current Students
Former Postdocs/Students
Research Group Alumni (Rotation, Independent Study, Project Mentoring) |
Recent Manuscripts |
Some but not all manuscripts are on arXiv. |
Bounding the Interleaving Distance for Mapper Graphs with a Loss
Function.
Erin W. Chambers, Elizabeth Munch, Sarah Percival, Bei Wang. Manuscript, 2023. arXiv:2307.15130 | |
Flexible and Probabilistic Topology Tracking with Partial Optimal Transport.
Mingzhe Li, Xinyuan Yan, Lin Yan, Tom Needham, Bei Wang. Manuscript, 2023. arXiv:2302.02895. | |
The SVD of Convolutional Weights: A CNN Interpretability Framework.
Brenda Praggastis, Davis Brown, Carlos Ortiz Marrero, Emilie Purvine, Madelyn Shapiro, Bei Wang. Manuscript, 2022. arXiv:2208.06894. | |
Intrinsic Interleaving Distance for Merge Trees.
Ellen Gasparovic, Elizabeth Munch, Steve Oudot, Katharine Turner, Bei Wang, Yusu Wang. Manuscript, 2019. arXiv:1908.00063. |
Recent Publications |
2024 | |
Labeled Interleaving Distance for Reeb Graphs.
Fangfei Lan, Salman Parsa, Bei Wang. Journal of Applied and Computational Topology, 2024. DOI:10.1007/s41468-024-00193-6 arXiv:2306.01186 | |
Distributed Augmentation, Hypersweeps, and Branch Decomposition of Contour Trees for Scientific Exploration.
Mingzhe Li, Hamish Carr, Oliver Rubel, Bei Wang, Gunther H. Weber. IEEE Visualization Conference (IEEE VIS), 2024. IEEE Transactions on Visualization and Computer Graphics, 2024. DOI:10.1109/TVCG.2024.3456322 arXiv:2408.04836 | |
Fast Comparative Analysis of Merge Trees Using Locality-Sensitive Hashing.
Weiran Lyu, Raghavendra Sridharamurthy, Jeff M. Phillips, Bei Wang. IEEE Visualization Conference (IEEE VIS), 2024. IEEE Transactions on Visualization and Computer Graphics, 2024. DOI:10.1109/TVCG.2024.3456383 arXiv:2409.08519 | |
MSz: An Efficient Parallel Algorithm for Correcting Morse-Smale Segmentations in Error-Bounded Lossy Compressors.
Yuxiao Li, Xin Liang, Bei Wang, Yongfeng Qiu, Lin Yan, Hanqi Guo. IEEE Visualization Conference (IEEE VIS), 2024. IEEE Transactions on Visualization and Computer Graphics, 2024. DOI:10.1109/TVCG.2024.3456337 Supplement 1. Supplement 2: Detailed figures from Figure 7 and Figure 8 in the main paper. arXiv:2406.09423 | |
Critical Point Extraction from Multivariate Functional Approximation.
Guanqun Ma, David Lenz, Tom Peterka, Hanqi Guo, Bei Wang. IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis) at IEEE VIS, 2024. arXiv:2408.13193 | |
ChannelExplorer: Visual Analytics at Activation Channel's Granularity (Poster).
Rahat Zaman, Bei Wang, Paul Rosen. IEEE Visualization Conference (IEEE VIS) Posters, 2024. | |
EulerMerge: Simplifying Euler Diagrams Through Set Merges.
Xinyuan Yan, Peter Rodgers, Peter Rottmann, Daniel Archambault, Jan-Henrik Haunert, Bei Wang. Proceedings of the 14th International Conference on the Theory and Application of Diagrams (DIAGRAMS), 2024. DOI:10.1007/978-3-031-71291-3_16 | |
PersiSort: A New Perspective on Adaptive Sorting Based on Persistence.
Jens Kristian Refsgaard Schou, Bei Wang. Proceedings of the 36th Canadian Conference on Computational Geometry (CCCG), 2024. Proceedings online. | |
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, Guo-Wei Wei, Ghada Zamzmi. Proceedings of the 41st International Conference on Machine Learning (ICML), 2024. arXiv:2402.08871 | |
Interpreting and generalizing deep learning in physics-based problems with functional linear models.
Amirhossein Arzani, Lingxiao Yuan, Pania Newell, Bei Wang. Engineering with Computers, 2024. DOI:10.1007/s00366-024-01987-z arXiv:2307.04569. | |
Topological Characterization and Uncertainty Visualization of Atmospheric Rivers.
Fangfei Lan, Brandi Gamelin, Lin Yan, Jiali Wang, Bei Wang, Hanqi Guo. Eurographics Conference on Visualization (EuroVis), 2024. Computer Graphics Forum, 43(3), e15084, 2024. DOI:10.1111/cgf.15084 | |
Generating Euler Diagrams Through Combinatorial Optimization.
Peter Rottmann, Peter Rodgers, Xinyuan Yan, Daniel Archambault, Bei Wang, Jan-Henrik Haunert. Eurographics Conference on Visualization (EuroVis), 2024. Computer Graphics Forum, 43(3), e15089, 2024. DOI:10.1111/cgf.15089 | |
In-Context Example Ordering Guided by Label Distributions.
Zhichao Xu, Daniel Cohen, Bei Wang, Vivek Srikumar. Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL), 2024. arXiv:2402.11447. | |
Labeled Interleaving Distance for Reeb Graphs (Abstract).
Fangfei Lan, Salman Parsa, Bei Wang. International Symposium on Computational Geometry (SOCG) Young Researcher Forum (YRF), 2024. | |
Computing Loss Function to Bound the Interleaving Distance for Mapper Graphs (Abstract).
Erin Wolf Chambers, Ishika Ghosh, Elizabeth Munch, Sarah Percival, Bei Wang. International Symposium on Computational Geometry (SOCG) Young Researcher Forum (YRF), 2024. | |
Measure-Theoretic Reeb Graphs and Reeb Spaces.
Qingsong Wang, Guanquan Ma, Raghavendra Sridharamurthy, Bei Wang. International Symposium on Computational Geometry (SOCG), 2024. DOI:10.4230/LIPIcs.SoCG.2024.80 arXiv:2401.06748. | |
Interactive Visualization of Time-Varying 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. | |
Exploring Visualization for Fairness in AI Education. Xinyuan Yan, Youjia Zhou, Arul Mishra, Himanshu Mishra, Bei Wang. IEEE Pacific Visualization Symposium (PacificVis), 2024. Supplementary Material. | |
2023 | |
TopoSZ: Preserving Topology in Error-Bounded 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 1302-1312, 2024. Supplementary Material. DOI:10.1109/TVCG.2023.3326920 arXiv:2304.11768. | |
TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclone.
Lin Yan, Hanqi Guo, Tom Peterka, Bei Wang, Jiali Wang. IEEE Visualization Conference (IEEE VIS), 2023. IEEE Transactions on Visualization and Computer Graphics (TVCG), 30, pages 1249-1259, 2024. Supplementary Material. DOI:10.1109/TVCG.2023.3326905 arXiv:2307.15243. | |
Hypergraph Co-Optimal Transport: Metric and Categorical Properties.
Samir Chowdhury, Tom Needham, Ethan Semrad, Bei Wang, Youjia Zhou. Journal of Applied and Computational Topology, 2023. DOI:10.1007/s41468-023-00142-9 arXiv:2112.03904 | |
Exploring Gradient Oscillation in Deep Neural Network Training.
Chedi Morchdi, Yi Zhou, Jie Ding, Bei Wang. 59th Annual Allerton Conference on Communication, Control, and Computing (ALLERTON), 2023. Allerton 2023 Program | |
Comparing Morse Complexes Using Optimal Transport:
An Experimental Study.
Mingzhe Li, Carson Storm, Austin Yang Li, Tom Needham, Bei Wang. IEEE Visualization and Visual Analytics (VIS) Short Paper, pages 41-45, 2023. Supplementary Material. DOI:10.1109/VIS54172.2023.00017 | |
From Flowchart to Questionnaire: Increasing Access to Justice via Visualization.
Youjia Zhou, Arul Mishra, Himanshu Mishra, Bei Wang IEEE Workshop on Visualization for Social Good (VIS4Good), pages 11-15, 2023. Supplementary Material. DOI:10.1109/VIS4Good60218.2023.00009 | |
Sketching Merge Trees for Scientific Visualization.
Mingzhe Li, Sourabh Palande, Lin Yan, Bei Wang. IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis) at IEEE VIS, pages 61-71, 2023. Supplementary Material. DOI:10.1109/TopoInVis60193.2023.00013 arXiv:2101.03196. | |
Combinatorial Exploration of Morse-Smale Functions on the Sphere via Interactive Visualization. Youjia Zhou, Janis Lazovskis, Michael J. Catanzaro, Matthew Zabka, Bei Wang. IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis) at IEEE VIS, pages 51-60, 2023. DOI:10.1109/TopoInVis60193.2023.00012 arXiv:1912.09580. | |
Homology-Preserving Multi-Scale Graph Skeletonization Using Mapper on Graphs. Mustafa Hajij, Bei Wang, Paul Rosen. IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis) at IEEE VIS, pages 10-20, 2023. Supplementary Material: User study data. DOI:10.1109/TopoInVis60193.2023.00008 arXiv:1804.11242. |
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Comparing Mapper Graphs of Artificial Neuron Activations. Youjia Zhou, Helen Jenne, Davis Brown, Madelyn Shapiro, Brett Jefferson, Cliff Joslyn, Gregory Henselman-Petrusek, Brenda Praggastis, Emilie Purvine, Bei Wang. IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis) at IEEE VIS, pages 41-50, 2023. DOI:10.1109/TopoInVis60193.2023.00011 |
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Metaboverse Enables Automated Discovery and Visualization of Diverse Metabolic Regulatory Patterns. Jordan A. Berg, Youjia Zhou, Yeyun Ouyang, Ahmad A. Cluntun, T. Cameron Waller, Megan E. Conway, Sara M. Nowinski, Tyler Van Ry, Ian George, James E. Cox, Bei Wang, Jared Rutter. Nature Cell Biology 25, pages 616-625, 2023. Download online. DOI:10.1038/s41556-023-01117-9 | |
Protein-Metabolite Interactomics of Carbohydrate Metabolism Reveal Regulation of Lactate Dehydrogenase. Kevin G. Hicks, Ahmad A. Cluntun, Heidi L. Schubert, Sean R. Hackett, Jordan A. Berg, Paul G. Leonard, Mariana A. Ajalla Aleixo, Youjia Zhou, Alex J. Bott, Sonia R. Salvatore, Fei Chang, Aubrie Blevins, Paige Barta, Samantha Tilley, Aaron Leifer, Andrea Guzman, Ajak Arok, Sarah Fogarty, Jacob M. Winter, Hee-Chul Ahn, Karen N. Allen, Samuel Block, Iara A. Cardoso, Jianping Ding, Ingrid Dreveny, Clarke Gasper, Quinn Ho, Atsushi Matsuura, Michael J. Palladino, Sabin Prajapati, PengKai Sun, Kai Tittmann, Dean R. Tolan, Judith Unterlass, Andrew P. VanDemark, Matthew G. Vander Heiden, Bradley A. Webb, Cai-Hong Yun, PengKai Zhap, Bei Wang, Francisco J. Schopfer, Christopher P. Hill, Maria Cristina Nonato, Florian L. Muller, James E. Cox, Jared Rutter. Science, 379 (6636), pages 996-1003, 2023. DOI: 10.1126/science.abm3452 | |
Visualizing and Analyzing the Topology of Neuron Activations in Deep Adversarial Training.
Youjia Zhou, Yi Zhou, Jie Ding, Bei Wang. Topology, Algebra, and Geometry in Machine Learning (TAGML) Workshop at ICML, 2023. OpenReview:Q692Q3dPMe. | |
VERB: Visualizing and Interpreting Bias Mitigation Techniques for Word Representations.
Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei Zhang, Bei Wang. ACM Transactions on Interactive Intelligent Systems, 14(1), pages 1-34, 2023. DOI: 10.1145/3604433 arXiv:2104.02797. | |
Multilevel Robustness for 2D Vector Field Feature Tracking, Selection, and Comparison. Lin Yan, Paul Aaron Ullrich, Luke P. Van Roekel, Bei Wang, Hanqi Guo. Computer Graphics Forum, 42(6), e14799, 2023. DOI: 10.1111/cgf.14799 arXiv:2209.11708 | |
TopoBERT: Exploring the Topology of Fine-Tuned Word Representations. Archit Rathore, Yichu Zhou, Vivek Srikumar, Bei Wang. Information Visualization, 22(3), pages 186-208, 2023. DOI: 10.1177/14738716231168671 | |
Visual Computer Cover of the Year 2023. Daniel Klötzl, Tim Krake, Youjia Zhou, Ingrid Hotz, Bei Wang, Daniel Weiskopf. Visual Computer, 2023. Based on Local Bilinear Computation of Jacobi Sets, Visual Computer 38, pages 3435-3448, 2022. | |
Meta-diagrams for 2-parameter persistence. Nate Clause, Tamal K. Dey, Facundo Mémoli, Bei Wang. International Symposium on Computational Geometry (SOCG), 2023. DOI:10.4230/LIPIcs.SoCG.2023.25 | |
Experimental Observations of the Topology of Convolutional Neural Network Activations. Emilie Purvine, Davis Brown, Brett Jefferson, Cliff Joslyn, Brenda Praggastis, Archit Rathore, Madelyn Shapiro, Bei Wang, Youjia Zhou. Proceedings of the 37th AAAI Conference on Artificial Intelligence (AAAI), 2023. DOI: 10.1609/aaai.v37i8.26134 arXiv:2212.00222 | |
Enable Decision Making for Battery Electric Bus Deployment Using Robust High-Resolution Interdependent Visualization. Gabrielius A. Kudirka, Xinyuan Yan, Sarah Kunzler, Yirong Zhou, Bei Wang, Xiaoyue Cathy Liu. Transportation Research Board (TRB) 102nd Annual Meeting, 2023. | |
2022 | |
An interactive visual demo of bias mitigation techniques for word representations from a Geometric Perspective.
Archit Rathore, Sunipa Dev, Jeff Phillips, Vivek Srikumar, Yan Zheng, Chin-Chia Michael Yeh, Junpeng Wang, Wei Zhang, Bei Wang. Proceedings of the NeurIPS 2021 Competitions and Demonstrations Track, PMLR,176, pages 330-334, 2022 Online: PMLR | |
Humans as Mitigators of Biases in Risk Prediction via Field Studies. Bei Wang, Arul Mishra, Himanshu Mishra. IEEE International Conference on Big Data (IEEE BigData), 2022. DOI: 10.1109/BigData55660.2022.10020306 | |
Uncertainty Visualization for Graph Coarsening. Fangfei Lan, Sourabh Palande, Michael Young, Bei Wang. IEEE International Conference on Big Data (IEEE BigData), 2022. DOI: 10.1109/BigData55660.2022.10021039 | |
Local Bilinear Computation of Jacobi Sets Daniel Klötzl, Tim Krake, Youjia Zhou, Ingrid Hotz, Bei Wang, Daniel Weiskopf. Computer Graphics International (CGI), 2022. Visual Computer, 38, pages 3435-3448, 2022. DOI: 10.1007/s00371-022-02557-4 Visual Computer Second Best Paper Award. | |
Reduced Connectivity for Local Bilinear Jacobi Sets.
Daniel Klötzl, Tim Krake, Youjia Zhou, Jonathan Stober, Kathrin Schulte, Ingrid Hotz, Bei Wang, Daniel Weiskopf. IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis) at IEEE VIS, 2022. DOI: 10.1109/TopoInVis57755.2022.00011 arXiv:2208.07148 Honorable Mention Paper Award. | |
Untangling Force-Directed Layouts Using Persistent Homology.
Bhavana Doppalapudi, Bei Wang, Paul Rosen. IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis) at IEEE VIS, 2022. DOI: 10.1109/TopoInVis57755.2022.00015 arXiv:2208.06927 | |
Geometry-Aware Merge Tree Comparisons for Time-Varying Data with Interleaving Distances.
Lin Yan, Talha Bin Masood, Farhan Rasheed, Ingrid Hotz, Bei Wang. IEEE Transactions on Visualization and Computer Graphics (TVCG), 2022. DOI: 10.1109/TVCG.2022.3163349 (early access) arXiv:2107.14373 | |
Topological Simplifications of Hypergraphs.
Youjia Zhou, Archit Rathore, Emilie Purvine, Bei Wang. IEEE Transactions on Visualization and Computer Graphics (TVCG), 2022. DOI: 10.1109/TVCG.2022.3153895 (early access) arXiv:2104.11214. | |
Discrete Stratified Morse Theory: Algorithms and A User's Guide Kevin Knudson and Bei Wang. Discrete & Computational Geometry (DCG), 2022. DOI:10.1007/s00454-022-00372-1 | |
Uncertainty Visualization of 2D Morse Complex Ensembles Using
Statistical Summary Maps.
Tushar Athawale, Dan Maljovec, Lin Yan, Chris R. Johnson, Valerio Pascucci, Bei Wang. IEEE Transactions on Visualization and Computer Graphics (TVCG), 28(4), pages 1955-1966, 2022. DOI: 10.1109/TVCG.2020.3022359 |
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Stitch Fix for Mapper and Topological Gains.
Youjia Zhou, Nathaniel Saul, Ilkin Safarli, Bala Krishnamoorthy, Bei Wang. Research in Computational Topology 2, Association for Women in Mathematics Series, vol 30, pages 265-294, Springer, Cham. 2022. Editors: Ellen Gasparovic, Vanessa Robins, Katharine Turner. DOI: 10.1007/978-3-030-95519-9_12 | |
Graph Pseudometrics from a Topological Point of View.
Ana Lucia Garcia-Pulido, Kathryn Hess, Jane Tan, Katharine Turner, Bei Wang, Naya Yerolemou. Research in Computational Topology 2, Association for Women in Mathematics Series, vol 30, pages 99-128, Springer, Cham. 2022. Editors: Ellen Gasparovic, Vanessa Robins, Katharine Turner. DOI: 10.1007/978-3-030-95519-9_5 | |
Local Versus Global Distances for Zigzag Persistence Modules.
Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier. Research in Computational Topology 2, Association for Women in Mathematics Series, vol 30, pages 265-294, Springer, Cham. 2022. Editors: Ellen Gasparovic, Vanessa Robins, Katharine Turner. DOI: 10.1007/978-3-030-95519-9_3 arXiv:1903.08298. | |
2021 | |
TopoAct: Visually Exploring the Shape of Activations in Deep Learning. Archit Rathore, Nithin Chalapathi, Sourabh Palande, Bei Wang. Computer Graphics Forum, 40(1), pages 382-397, 2021. Supplemental Material. DOI: 10.1111/cgf.14195 arXiv:1912.06332. | |
Adaptive Covers for Mapper Graphs Using Information Criteria. Nithin Chalapathi, Youjia Zhou, Bei Wang. IEEE International Conference on Big Data (IEEE BigData), Workshop on Applications of Topological Data Analysis to Big Data, 2021. DOI: 10.1109/BigData52589.2021.9671324 | |
Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, and Educating the Earth. Fangfei Lan, Michael Young, Lauren Anderson, Anders Ynnerman, Alexander Bock, Michelle A. Borkin, Angus G. Forbes, Juna A. Kollmeier, Bei Wang. Eurographics Conference on Visualization (EuroVis), 2021. Computer Graphics Forum, 40(3), pages 635-663, 2021. DOI: 10.1111/cgf.14332 | |
Scalar Field Comparison with Topological Descriptors: Properties and Applications for Scientific Visualization.
Lin Yan, Talha Bin Masood, Raghavendra Sridharamurthy, Farhan Rasheed, Vijay Natarajan, Ingrid Hotz, Bei Wang. Eurographics Conference on Visualization (EuroVis), 2021. Computer Graphics Forum, 40(3), pages 599-633, 2021. DOI: 10.1111/cgf.14331 | |
Pheno-Mapper: An Interactive Toolbox for the Visual Exploration of Phenomics Data.
Youjia Zhou, Methun Kamruzzaman, Patrick Schnable, Bala Krishnamoorthy, Ananth Kalyanaraman, Bei Wang. Proceedings of the 12th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM BCB), Article No. 20, pages 1-10, 2021. DOI: 10.1145/3459930.3469511 | |
Mapper Interactive: A Scalable, Extendable, and Interactive Toolbox for the Visual Exploration of High-Dimensional Data. Youjia Zhou, Nithin Chalapathi, Archit Rathore, Yaodong Zhao, Bei Wang. IEEE Pacific Visualization Symposium, 2021. DOI: 10.1109/PacificVis52677.2021.00021 arXiv:2011.03209. | |
A Visual Tour of Bias Mitigation Techniques for Word Representations (Tutorial Overview)
Archit Rathore, Sunipa Dev, Jeff M. Phillips, Vivek Srikumar, Bei Wang Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining, pages 4064-4065, 2021. DOI: 10.1145/3447548.3470807 | |
Spatio-Temporal Visualization of Interdependent Battery Bus Transit and Power Distribution Systems.
Avishan Bagherinezhad, Michael Young, Bei Wang, Masood Parvania. IEEE PES Innovative Smart Grid Technologies Conference (ISGT), 2021. DOI: 10.1109/ISGT49243.2021.9372185 | |
Probabilistic Convergence and Stability of Random Mapper Graphs.
Adam Brown, Omer Bobrowski, Elizabeth Munch, Bei Wang. Journal of Applied and Computational Topology, 5, pages 99-140, 2021. DOI:10.1007/s41468-020-00063-x arXiv:1909.03488. | |
Electrum: Visualization, Analysis, and Contextualization of High-Throughput Protein-Metabolite Interaction Datasets (Abstract).
Jordan A. Berg, Ian George, Youjia Zhou, Kevin G. Hicks, Bei Wang, Jared Rutter. Intelligent Systems for Molecular Biology and European Conference on Computational Biology (ISMB/ECCB), 2021. | |
2020 | |
Modeling and Identifying Regulatory Patterns within Chaotic Metabolic Networks (Abstract).
Jordan A. Berg, Youjia Zhou, Bei Wang, Jared Rutter. Intelligent Systems for Molecular Biology (ISMB), 2020. Youtube Video. | |
Towards Spectral Sparsification of Simplicial Complexes Based on Generalized Effective Resistance.
Braxton Osting, Sourabh Palande and Bei Wang. Journal of Computational Geometry, 11(1), pages 176-211, 2020. Online: Journal of Computational Geometry. DOI: 10.20382/jocg.v11i1a8 arXiv:1708.08436. | |
State of the Art in Time-Dependent Flow Topology: Interpreting Physical Meaningfulness Through Mathematical Properties.
Roxana Bujack, Lin Yan, Ingrid Hotz, Christoph Garth, Bei Wang. Eurographics Conference on Visualization (EuroVis) STAR Computer Graphics Forum, 39(3), pages 811-835, 2020. DOI: 10.1111/cgf.14037 | |
Sheaf-Theoretic Stratification Learning From Geometric and Topological Perspectives.
Adam Brown and Bei Wang. Discrete & Computational Geometry, 2020. DOI:10.1007/s00454-020-00206-y arXiv:1712.07734 | |
On Homotopy Types of Vietoris--Rips Complexes of Metric Gluings.
Michal Adamaszek, Henry Adams, Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang and Lori Ziegelmeier. Journal of Applied and Computational Topology, 4, pages 425-454, 2020. DOI:10.1007/s41468-020-00054-y arXiv:1712.06224. | |
Moduli Spaces of Morse Functions for Persistence.
Michael J. Catanzaro, Justin Curry, Brittany Terese Fasy, Janis Lazovskis, Greg Malen, Hans Riess, Bei Wang, Matthew Zabka. Journal of Applied and Computational Topology, 4, pages 353-385, 2020. DOI:10.1007/s41468-020-00055-x arXiv:1909.10623. | |
Mathematical Foundations in Visualization.
Ingrid Hotz, Roxana Bujack, Christoph Garth, Bei Wang. In Foundations of Data Visualization, pages 87-119, Springer, 2020 Editors: Min Chen, Helwig Hauser, Penny Rheingans, Gerik Scheuermann. DOI:10.1007/978-3-030-34444-3_5 | |
Interactive Visualization of Interdependent Power and Water Infrastructure Operation. Han Han, Konstantinos Oikonomou, Nithin Chalapathi, Masood Parvania, Bei Wang. IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 2020. DOI:10.1109/ISGT45199.2020.9087680 | |
Topological Inference of Manifolds with Boundary.
Yuan Wang, Bei Wang. Computational Geometry: Theory and Applications, 88(101606), 2020. DOI:10.1016/j.comgeo.2019.101606 arXiv:1810.05759 | |
Visual Demo of Discrete Stratified Morse Theory (Media Exposition)
Youjia Zhou, Kevin Knudson, Bei Wang. International Symposium on Computational Geometry (SoCG), 2020. DOI: 10.4230/LIPIcs.SoCG.2020.82 | |
Learning With Topological Features of Functional Brain Networks (Abstract).
Sourabh Palande, Bei Wang. Algebraic Topology: Methods, Computation, & Science (ATMCS), poster, 2020. | |
A Visual Exploration and Design of Morse Vector Fields (Abstract).
Youjia Zhou, Janis Lazovskis, Michael J. Catanzaro, Matthew Zabka, Bei Wang. Algebraic Topology: Methods, Computation, & Science (ATMCS), poster, 2020. | |
Persistent Homology Guided Force-Directed Graph Layouts.
Ashley Suh, Mustafa Hajij, Bei Wang, Carlos Scheidegger, Paul Rosen IEEE Transactions on Visualization and Computer Graphics (TVCG, Proceedings of InfoVis), 26(1), pages 697-707, 2020. DOI: 10.1109/TVCG.2019.2934802 arXiv:1712.05548 Long Video. Short Video. |
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A Structural Average of Labeled Merge Trees for Uncertainty Visualization.
Lin Yan, Yusu Wang, Elizabeth Munch, Ellen Gasparovic, Bei Wang. IEEE Transactions on Visualization and Computer Graphics (TVCG, Proceedings of SciVis), 26(1), pages 832-842, 2020. Supplemental Material. Doi: 10.1109/TVCG.2019.2934242 arXiv:1908.00113 Long Video. Short Video. |
2019 | |
The Relationship Between the Intrinsic Cech and Persistence Distortion Distances for Metric Graphs.
Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier. Journal of Computational Geometry, 10(1), pages 477-499, 2019. DOI: 10.20382/jocg.v10i1a16 arXiv:1812.05282 | |
A Kernel for Multi-Parameter Persistent Homology.
René Corbet, Ulderico Fugacci, Michael Kerber, Claudia Landi, Bei Wang. Shape Modeling International (SMI), 2019. Computers & Graphics: X, 2, 100005, 2019. DOI:10.1016/j.cagx.2019.100005 arXiv:1809.10231 Best Paper Award at SMI 2019! | |
Persistence-Driven Design and Visualization of Morse Vector Fields (Extended Abstract) Youjia Zhou, Janis Lazovskis, Michael J. Catanzaro, Matthew Zabka, Bei Wang. China Visualization and Visual Analytics Conference (ChinaVis), 2019. Best Poster Award at ChinaVis 2019! | |
Autism Classification Using Topological Features and Deep Learning: A Cautionary Tale.
Archit Rathore, Sourabh Palande, Jeffrey Anderson, Brandon Zielinski, Tom Fletcher, Bei Wang. 22nd International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), 2019. Supplemental Material DOI:10.1007/978-3-030-32248-9_82 | |
Robust Extraction and Simplification of 2D Symmetric Tensor Field Topology. Jochen Jankowai, Bei Wang, Ingrid Hotz. Eurographics Conference on Visualization (EuroVis), 2019. Computer Graphics Forum (CGF), 38(3), pages 337-349, 2019. DOI:10.1111/cgf.13693 | |
Using Contour Trees in the Analysis and Visualization of Radio Astronomy Data Cubes.
Paul Rosen, Anil Seth, Betsy Mills, Adam Ginsburg, Julia Kamenetzky, Jeff Kern, Chris R. Johnson, Bei Wang. Topology-Based Methods in Visualization (TopoInVis), 2019. arXiv:1704.04561. | |
Topology, Computation and Data Analysis (Dagstuhl Seminar 19212) Editors: Michael Kerber, Vijay Natarajan, Bei Wang. Report from Dagstuhl Seminar, 2019. DOI: 10.4230/DagRep.9.5.110 | |
Revisiting Abnormalities in Brain Network Architecture Underlying Autism Using Topology-Inspired Statistical Inference.
Sourabh Palande, Vipin Jose, Brandon Zielinski, Jeffrey Anderson, P. Thomas Fletcher and Bei Wang. International Workshop on Connectomics in NeuroImaging (CNI) at MICCAI, 2017. Brain Connectivity, 9(1):13-21, 2019 DOI: 10.1089/brain.2018.0604 |
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Interpreting Galilean Invariant Vector Field Analysis via Extended Robustness.
Bei Wang, Roxana Bujack, Paul Rosen, Primoz Skraba, Harsh Bhatia and Hans Hagen. In Topological Methods in Data Analysis and Visualization V: Theory, Algorithms, and Applications (Proceedings of TopoInVis 2017). Springer, 2019. DOI: 10.1007/978-3-030-43036-8. | |
2018 | |
Topological Data Analysis of Functional MRI Connectivity in Time and
Space Domains.
Keri Anderson, Jeffrey Anderson, Sourabh Palande, and Bei Wang. International Workshop on Connectomics in NeuroImaging (CNI) at MICCAI, 2018. Connectomics Neuroimaging (Lecture Notes in Computer Science, Proceedings of International Workshop on Connectomics in NeuroImaging), volume 11083. Springer, 2018. Supplemental Material. DOI: 10.1007/978-3-030-00755-3_8 Best Paper Award at CNI 2018! |
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Homology-Preserving Dimensionality Reduction via Manifold Landmarking and Tearing.
Lin Yan, Yaodong Zhao, Paul Rosen, Carlos Scheidegger, Bei Wang. Symposium on Visualization in Data Science (VDS) at IEEE VIS, 2018. arXiv:1806.08460 |
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Discrete Stratified Morse Theory: A User's Guide.
Kevin Knudson and Bei Wang. International Symposium on Computational Geometry (SOCG), 2018. DOI: 10.4230/LIPIcs.SoCG.2018.54 arXiv:1801.03183 | |
Sheaf-Theoretic Stratification Learning.
Adam Brown and Bei Wang. International Symposium on Computational Geometry (SOCG), 2018. DOI: 10.4230/LIPIcs.SoCG.2018.14 arXiv:1712.07734 | |
Vietoris-Rips and Čech Complexes of Metric Gluings.
Michal Adamaszek, Henry Adams, Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang and Lori Ziegelmeier. International Symposium on Computational Geometry (SOCG), 2018. DOI: 10.4230/LIPIcs.SoCG.2018.3 arXiv:1712.06224 | |
Visual Detection of Structural Changes in Time-Varying Graphs Using Persistent Homology.
Mustafa Hajij, Bei Wang, Carlos Scheidegger, Paul Rosen. Proceedings IEEE Pacific Visualization Symposium (PacificVis), 2018. DOI: 10.1109/PacificVis.2018.00024 arXiv:1707.06683 | |
Topology, Computation and Data Analysis (Dagstuhl Seminar 17292) Editors: Hamish Carr, Michael Kerber, and Bei Wang. Report from Dagstuhl Seminar, 2018. DOI: 10.4230/DagRep.7.7.88 | |
Visual Exploration of Semantic Relationships in Neural Word Embeddings.
Shusen Liu, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Vivek Srikumar, Bei Wang, Yarden Livnat and Valerio Pascucci. IEEE Transactions on Visualization and Computer Graphics (TVCG, Proceedings of InfoVis), 24(1):553-562, 2018. DOI:10.1109/TVCG.2017.2745141 | |
A Complete Characterization of the 1-DimensionalIntrinsic Čech Persistence Diagrams for Metric Graphs.
Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang and Lori Ziegelmeier. Research in Computational Topology, Pages 33-56, 2018. DOI: 10.1007/978-3-319-89593-2 arXiv:1512.04108. | |
2017 | |
Visualizing Sensor Network Coverage with Location Uncertainty.
Tim Sodergren, Jessica Hair, Jeff M. Phillips and Bei Wang. Symposium on Visualization in Data Science (VDS) at IEEE VIS, 2017. DOI: 10.1109/VDS.2017.8573448 ArXiv:1710.06925 | |
Open Problems in Computational Topology.
Brittany Terese Fasy and Bei Wang (with contributions by members of the WinCompTop community). SIGACT NEWS Open Problems Column, Edited by Bill Gasarch, 48(3), 2017. Online Version: SIGACT NEWS open problems column. | |
Robustness for 2D Symmetric Tensor Field Topology.
Bei Wang and Ingrid Hotz. Modeling, Analysis, and Visualization of Anisotropy, Springer, 2017. | |
Exploring the Evolution of Pressure-Perturbations to
Understand Atmospheric Phenomena.
Wathsala Widanagamaachchi, Alexander Jacques, Bei Wang, Erik Crosman, Peer-Timo Bremer, Valerio Pascucci and John Horel. Proceedings IEEE Pacific Visualization Symposium (PacificVis), 2017. DOI: 10.1109/PACIFICVIS.2017.8031584 | |
Visualizing High-Dimensional Data: Advances in the Past Decade.
Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer and Valerio Pascucci IEEE Transactions on Visualization and Computer Graphics (TVCG), 23(3), pages 1249-1268, 2017. DOI: 10.1109/TVCG.2016.2640960 Survey Website (Maintained by Shusen Liu). | |
2016 | |
Visual Exploration of Multiway Dependencies in Multivariate Data.
Hoa Nguyen, Paul Rosen and Bei Wang. ACM SIGGRAPH ASIA Symposium on Visualization, pages 1-8, 2016. DOI: 10.1145/3002151.3002162 | |
Convergence between Categorical Representations of Reeb Space and Mapper.
Elizabeth Munch and Bei Wang*. International Symposium on Computational Geometry (SOCG), 2016. arXiv:1512.04108. Invited Talk at TGDA@OSU. | |
Kernel Partial Least Squares Regression for Relating Functional Brain Network Topology to Clinical Measures of Behavior.
Eleanor Wong, Sourabh Palande, Bei Wang, Brandon Zielinski, Jeffrey Anderson and P. Thomas Fletcher. International Symposium on Biomedical Imaging (ISBI), 2016. DOI: 10.1109/ISBI.2016.7493506 | |
Grassmannian Atlas: A General Framework for Exploring Linear Projections of High-Dimensional Data.
Shusen Liu, Peer-Timo Bremer, Jayaraman J. Thiagarajan, Bei Wang, Brian Summa and Valerio Pascucci. Eurographics Conference on Visualization (EuroVis), 2016. Computer Graphics Forum (CGF), 35(3), pages 1-10, 2016. DOI: 10.1111/cgf.12876 | |
Exploring Persistent Local Homology in Topological Data Analysis.
Brittany T. Fasy and Bei Wang*. Special session on Topological Methods in Data Science and Analysis, IEEE International Conference on Acoustics, Speech and Signal Process (ICASSP), 2016. | |
Critical Point Cancellation in 3D Vector Fields: Robustness and Discussion.
Primoz Skraba, Paul Rosen, Bei Wang, Guoning Chen, Harsh Bhatia and Valerio Pascucci. IEEE Pacific Visualization (PacificVis), 2016. IEEE Transactions on Visualization and Computer Graphics (TVCG), 22(6), pages 1683-1693, 2016. DOI: 10.1109/TVCG.2016.2534538 Supplemental Video. Vortex Video. Best Paper Award at PacificVis 2016! | |
Topology-Inspired Partition-Based Sensitivity Analysis and Visualization of Nuclear Simulations.
Daniel Maljovec, Bei Wang, Paul Rosen, Andrea Alfonsi, Giovanni Pastore, Cristian Rabiti and Valerio Pascucci. Proceedings IEEE Pacific Visualization (PacificVis), 2016. | |
Analyzing Simulation-Based PRA Data Through
Traditional and Topological Clustering: A BWR Station Blackout Case Study.
Dan Maljovec, Shusen Liu, Bei Wang, Valerio Pascucci, Peer-Timo Bremer, Diego Mandelli and Curtis Smith. Reliability Engineering & System Safety (RESS), 145, pages 262-276, 2016. Online Version: invited longer journal version based on our work from PSAM 2014. | |
2015 | |
Reeb Space Approximation with Guarantees (Abstract).
Elizabeth Munch and Bei Wang*. 25th Annual Fall Workshop on Computational Geometry (FWCG), 2015. Proceedings Online. | |
Geometric Inference on Kernel Density Estimates.
Jeff M. Phillips, Bei Wang and Yan Zheng. International Symposium on Computational Geometry (SOCG), 2015. Conference Proceedings. Full Version: arXiv:1307.7760. | |
Local, Smooth, and Consistent Jacobi Set Simplification.
Harsh Bhatia, Bei Wang, Gregory Norgard, Valerio Pascucci and Peer-Timo Bremer. Computational Geometry: Theory and Applications (CGTA), 48(4), pages 311-332, 2015. Online Version. |
Interstitial and Interlayer Ion Diffusion Geometry Extraction in Graphitic Nanosphere Battery Materials.
Attila Gyulassy, Aaron Knoll, Kah Chun Lau, Bei Wang, Peer-Timo Bremer, Michael E. Papka, Larry A. Curtiss and Valerio Pascucci. Proceedings IEEE Visualization Conference (VIS), 2015. IEEE Transactions on Visualization and Computer Graphics (TVCG), 22(1), pages 916 - 925, 2016. |
Robustness-Based Simplification of 2D Steady and Unsteady Vector Fields.
Primoz Skraba, Bei Wang, Guoning Chen and Paul Rosen. IEEE Transactions on Visualization and Computer Graphics (TVCG), 21(8), pages 930 - 944, 2015. Supplemental Material. Supplemental Video. | |
Visualizing High-Dimensional Data: Advances in the Past Decade.
Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer and Valerio Pascucci. Eurographics Conference on Visualization (EuroVis) STAR, 2015. Survey Website. | |
Visual Exploration of High-Dimensional Data through Subspace Analysis and Dynamic Projections.
Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer and Valerio Pascucci. Eurographics Conference on Visualization (EuroVis) , 2015. Computer Graphics Forum (CGF), 34(3), pages 271-280, 2015. Supplemental Video. Journal Online. YouTube. |
Morse-Smale Analysis of Ion Diffusion for DFT Battery Materials Simulations.
Attila Gyulassy, Aaron Knoll, Kah Chun Lau, Bei Wang, Peer-Timo Bremer, Michael E. Papka, Larry A. Curtiss and Valerio Pascucci. Topology-Based Methods in Visualization (TopoInVis) , 2015. |
ND2AV: N-Dimensional Data Analysis and Visualization -- Analysis for the National Ignition Campaign.
Peer-Timo Bremer, Dan Maljovec, Avishek Saha, Bei Wang, Jim Gaffney, Brian K. Spears and Valerio Pascucci. Computing and Visualization in Science (CVS), 17(1), Pages 1-18, 2015. Online Version. Supplementary Video. | |
2014 | |
Approximating Local Homology from Samples.
Primoz Skraba and Bei Wang*. Proceedings 25th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 174-192, 2014. SIAM Proceedings Online. | |
2D Vector Field Simplification Based on Robustness.
Primoz Skraba, Bei Wang, Guoning Chen and Paul Rosen. Proceedings IEEE Pacific Visualization (PacificVis), 2014. PacificVis Supplemental. Best Paper Award at PacificVis 2014! | |
Interpreting Feature Tracking Through the Lens of Robustness.
Primoz Skraba and Bei Wang*. Topological Methods in Data Analysis and Visualization III: Theory, Algorithms, and Applications, pages 19-38, 2014. Workshop Version: Topology-Based Methods in Visualization (TopoInVis), 2013. | |
Multivariate Volume Visualization through Dynamic Projections.
Shusen Liu, Bei Wang, Jayaraman J. Thiagarajan, Peer-Timo Bremer and Valerio Pascucci. IEEE Symposium on Large Data Analysis and Visualization (LDAV), 2014. LDAV Video. YouTube. | |
Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data.
Shusen Liu, Bei Wang, Peer-Timo Bremer and Valerio Pascucci. Eurographics Conference on Visualization (EuroVis), 2014. Computer Graphics Forum (CGF), 33(3), pages 101-110, 2014. EuroVis Supplemental. EuroVis Video. Journal Online. YouTube. Software: DataExplorerHD v0.1 (Maintained by Shusen Liu) | |
Analyzing Simulation-Based PRA Data Through Clustering: a BWR
Station Blackout Case Study.
Dan Maljovec, Shusen Liu, Bei Wang, Valerio Pascucci, Peer-Timo Bremer, Diego Mandelli and Curtis Smith. Probabilistic Safety Assessment & Management conference (PSAM), 2014. Proceedings Online. | |
Overview of New Tools to Perform Safety Analysis: BWR Station Black Out Test Case.
Diego Mandelli, Curtis Smith, Tom Riley, Joseph Nielsen, John Schroeder, Cristian Rabiti, Andrea Alfonsi, Joshua Cogliati, Robert Kinoshita, Valerio Pascucci, Bei Wang, Dan Maljovec. Probabilistic Safety Assessment & Management conference (PSAM) , 2014. Proceedings Online. | |
2013 | |
Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields.
Bei Wang, Paul Rosen, Primoz Skraba, Harsh Bhatia, Valerio Pascucci. Eurographics Conference on Visualization (EuroVis) 2013. Computer Graphics Forum (CGF), 32(2), pages 221-230, 2013. EuroVis Supplemental. EuroVis Video. CEDMAV Video. Journal Online. | |
Adaptive Sampling with Topological Scores.
Dan Maljovec, Bei Wang, Ana Kupresanin, Gardard Johannesson, Valerio Pascucci, Peer-Timo Bremer International Journal for Uncertainty Quantification (IJUQ), 3(2), pages 119-141, 2013. Workshop version: Working with Uncertainty Workshop at IEEE VisWeek, 2011. | |
Exploration of High-Dimensional Scalar Function
for Nuclear Reactor Safety Analysis and Visualization.
Dan Maljovec, Bei Wang, Valerio Pascucci, Peer-Timo Bremer, Michael Pernice, Diego Mandelli and Robert Nourgaliev. Proceedings International Conference on Mathematics and Computational Methods Applied to Nuclear Science & Engineering (M&C), pages 712-723, 2013. | |
Adaptive Sampling Algorithms for Probabilistic Risk Assessment of
Nuclear Simulations.
Dan Maljovec, Bei Wang, Diego Mandelli, Peer-Timo Bremer and Valerio Pascucci. International Topical Meeting on Probabilistic Safety Assessment and Analysis (PSA), 2013. First runner-up for the Best Student Paper Award! | |
Analyze Dynamic Probabilistic Risk Assessment Data through Clustering.
Dan Maljovec, Bei Wang, Diego Mandelli, Peer-Timo Bremer and Valerio Pascucci. International Topical Meeting on Probabilistic Safety Assessment and Analysis (PSA), 2013. | |
2012 | |
Local Homology Transfer and Stratification Learning.
Paul Bendich, Bei Wang and Sayan Mukherjee. Proceedings 23rd Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 1355-1370, 2012. Full version: arXiv:1008.3572 . A revised journal full version is coming soon! |
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Kernel Distance for Geometric Inference (Abstract).
Jeff M. Phillips and Bei Wang*. 22nd Annual Fall Workshop on Computational Geometry (FWCG), 2012. | |
Topological Analysis and Visualization of Cyclical Behavior in Memory Reference Traces.
A.N.M. Imroz Choudhury, Bei Wang, Paul Rosen and Valerio Pascucci. Proceedings IEEE Pacific Visualization (PacificVis), 2012. Supplemental Video. PacificVis Online. | |
2011 | |
Branching and Circular Features in High Dimensional Data.
Bei Wang, Brian Summa, Valerio Pascucci and Mikael Vejdemo-Johansson Proceedings IEEE Visualization Conference (VIS), 2011. IEEE Transactions on Visualization and Computer Graphics (TVCG), 17(12), pages 1902-1911, 2011. | |
Computing Elevation Maxima by Searching the Gauss Sphere. Bei Wang, Herbert Edelsbrunner and Dmitriy Morozov. Journal of Experimental Algorithmics (JEA), 16, pages 1-13, 2011. Conference Version: Proceedings of the 13th International Symposium on Experimental Algorithms (SEA), 2009; Lecture Notes in Computer Science (LNCS), 5526, pages 281-292, 2009. | |
2010 | |
Separating Features from Noise with Persistence and Statistics. Bei Wang. Ph.D. Thesis, Duke University, 2010. | |
A Computational Screen for Site Selective A-to-I Editing Detects
Novel Sites in Neuron Specific Hu Proteins. Mats Ensterö, Örjan Åkerborg, Daniel Lundin, Bei Wang, Terrence S Furey, Marie Öhman and Jens Lagergren. BMC Bioinformatics, 11(6), 2010. | |
Towards Stratification Learning through Homology Inference. Paul Bendich, Sayan Mukherjee and Bei Wang. AAAI Fall Symposium on Manifold Learning and its Applications (AAAI), 2010. Manifold Learning and its Applications: Papers from the AAAI Fall Symposium. | |
2008 | |
Spatial Scan Statistics for Graph Clustering. Bei Wang, Jeff M. Phillips, Robert Schrieber, Dennis Wilkinson, Nina Mishra and Robert Tarjan. Proceedings of 8th SIAM International Conference on Data Mining (SDM), 2008. | |
2007 | |
Two Proteins for the Price of One: The Design of Maximally Compressed Coding Sequences. Bei Wang, Dimitris Papamichail, Steffen Mueller and Steven Skiena. Natural Computing, 6(4), pages 359-370, 2007. Conference Version: Proceedings of the 11th International Meeting on DNA Computing (DNA), 2005; Lecture Notes in Computer Science (LNCS), 3892, pages 387-398, 2006. | |
2006 | |
A Framework for Modeling DNA Based Molecular Systems. Sudheer Sahu, Bei Wang and John H. Reif. Proceedings 12th International Meeting on DNA Computing (DNA), 2006. Lecture Notes in Computer Science (LNCS), 4287, pages 250-265, 2006. |
Undergraduate Research |
Experimental Robot Musicians. Tarek M. Sobh, Bei Wang and Kurt W. Coble. Journal of Intelligent and Robotic System (JIRS), 38(2), pages 197-212, 2003. DOI: 10.1023/A:1027319831986 | |
Web Enabled Robot Design and Dynamic Control Simulation Software Solutions from Task Points Description. Tarek M. Sobh, Bei Wang, and Sarosh H. Patel. Proceedings of the 29th Annual International Conference of the IEEE Industrial Electronics Society (IECON), 2003. DOI: 10.1109/IECON.2003.1280227 | |
A Mobile Wireless and Web-based Analysis Tool for Robot Design and Dynamic Control Simulation from Task Points Description. Tarek M. Sobh, Bei Wang and Sarosh Patel. Journal of Internet Technology, 4(3), pages 153-161, 2003. | |
Web Based Remote Surveillance of Mobile Robot. Tarek M. Sobh, Rajeev Sanyal and Bei Wang. Journal of Internet Technology, 4(3), pages 179-184, 2003. |
Miscellaneous |
Topology-Based Active Learning.
Dan Maljovec, Bei Wang, John Moeller and Valerio Pascucci. SCI Technical Report UUSCI-2014-00, 2014. |
A Comparative Study of Morse Complex Approximation Using Different
Neighborhood Graphs.
Dan Maljovec, Avishek Saha, Peter Lindstrom, Peer-Timo Bremer, Bei Wang, Carlos Correa, and Valerio Pascucci. Topology-Based Methods in Visualization (TopoInVis), 2013. |
Invited Talks |
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Extra |