Bei Wang

Data Analysis and Data Visualization

Publications

Journal Publications / Book Chapters

1. Critical Point Cancellation in 3D Vector Fields: Robustness and Discussion.
   Primoz Skraba, Paul Rosen, Bei Wang, Guoning Chen, Harsh Bhatia and Valerio Pascucci.
   IEEE Transactions on Visualization and Computer Graphics (TVCG), 22(6), pages 1683-1693, 2016.
   [PDF] [Supplemental Video] [Vortex Video]


2. 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.
   IEEE Transactions on Visualization and Computer Graphics (TVCG), 22(1), pages 916 - 925, 2016.
   [PDF]


3. 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.
   [PDF] [Online Version]


4. 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.
   [PDF] [Supplemental Material] [Supplemental Video]


5. 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.
   [PDF] [Online Version]


6. 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.
   [PDF] [Online Version] [Supplementary Video]


7. 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.
   Computer Graphics Forum (CGF), 34(3), pages 271-280, 2015.
   [PDF] [Supplemental Video] [Journal Online] [YouTube]


8. Distortion-Guided Structure-Driven Interactive Exploration of High-Dimensional Data.
   Shusen Liu, Bei Wang, Peer-Timo Bremer and Valerio Pascucci.
   Computer Graphics Forum (CGF), 33(3), pages 101-110, 2014.
   [PDF] [EuroVis Supplemental] [EuroVis Video] [Journal Online] [YouTube] [Software: DataExplorerHD v0.1 (Maintained by Shusen Liu)]


9. 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.
   [PDF]


10. Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields.
    Bei Wang, Paul Rosen, Primoz Skraba, Harsh Bhatia and Valerio Pascucci.
    Computer Graphics Forum (CGF), 32(2), pages 221-230, 2013.
    [PDF] [EuroVis Supplemental] [EuroVis Video] [CEDMAV Video] [Journal Online]


11. 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.
    [PDF]


12. Branching and Circular Features in High Dimensional Data.
    Bei Wang, Brian Summa, Valerio Pascucci and Mikael Vejdemo-Johansson
    IEEE Transactions on Visualization and Computer Graphics (TVCG), 17(12), pages 1902-1911, 2011.
    [PDF]


13. 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.
    [PDF]


14. 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.
    [PDF]


15. 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.
    [PDF]


16. 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.
    [PDF]


17. 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.
    [PDF]


18. 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.
    [PDF]

Conference Publications

1. Convergence between Categorical Representations of Reeb Space and Mapper.
   Elizabeth Munch and Bei Wang*.
   International Symposium on Computational Geometry (SOCG), 2016.
   [PDF] [arXiv:1512.04108] [Invited Talk TGDA@OSU]
   


2. 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.
   [PDF] [Poster Presentation]


3. 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.
   [PDF]


4. 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.
   [PDF]


5. Critical Point Cancellation in 3D Vector Fields: Robustness and Discussion.
   Primoz Skraba, Paul Rosen, Bei Wang, Guoning Chen, Harsh Bhatia and Valerio Pascucci.
   Proceedings IEEE Pacific Visualization (PacificVis), 2016.
   Best Paper Award!
   [PDF] [Supplemental Video] [Vortex Video]


6. 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.
   [PDF]


7. Geometric Inference on Kernel Density Estimates.
   Jeff M. Phillips, Bei Wang and Yan Zheng*.
   International Symposium on Computational Geometry (SOCG), 2015.
   [PDF] [Conference Proceedings] [Full Version: arXiv:1307.7760]


8. 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.
   [PDF]


9. 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 -- State of The Art Report, 2015.
   [PDF] [Survey Website]


10. 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.
    [PDF] [Supplemental Video] [Journal Online] [YouTube]


11. Approximating Local Homology from Samples.
    Primoz Skraba and Bei Wang*.
    Proceedings 25th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA), pages 174-192, 2014.
    [PDF] [SIAM Proceedings Online]


12. 2D Vector Field Simplification Based on Robustness.
    Primoz Skraba, Bei Wang, Guoning Chen and Paul Rosen.
    Proceedings IEEE Pacific Visualization (PacificVis), 2014.
    Best Paper Award!
    [PDF] [PacificVis Supplemental]


13. 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.
    [PDF] [LDAV Video] [YouTube]


14. 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.
    [PDF] [Proceedings Online]


15. 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 and Dan Maljovec.
    Probabilistic Safety Assessment & Management conference (PSAM) , 2014.
    [PDF] [Proceedings Online]


16. 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.
    [PDF] [EuroVis Supplemental] [EuroVis Video] [Journal Online] [YouTube] [Software: DataExplorerHD v0.1 (Maintained by Shusen Liu)]


17. Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields.
    Bei Wang, Paul Rosen, Primoz Skraba, Harsh Bhatia and Valerio Pascucci.
    Eurographics Conference on Visualization (EuroVis) 2013.
    [PDF] [EuroVis Supplemental] [EuroVis Video] [CEDMAV Video] [Journal Online]


18. 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.
    [PDF]


19. 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!
    [PDF]


20. 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.
    [PDF]


21. 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.
    [PDF] [Full version: arXiv:1008.3572]


22. 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.
    [PDF] [Supplemental Video] [PacificVis Online]


23. Branching and Circular Features in High Dimensional Data.
    Bei Wang, Brian Summa, Valerio Pascucci and Mikael Vejdemo-Johansson
    Proceedings IEEE Visualization Conference (VIS), 2011.
    [PDF]


24. Computing Elevation Maxima by Searching the Gauss Sphere.
    Bei Wang, Herbert Edelsbrunner and Dmitriy Morozov.
    Proceedings of the 13th International Symposium on Experimental Algorithms (SEA), 2009;
    Lecture Notes in Computer Science (LNCS), 5526, pages 281-292, 2009.
    [PDF]


25. 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.
    [PDF]


26. 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.
    [PDF]


27. Two Proteins for the Price of One: The Design of Maximally Compressed Coding Sequences.
    Bei Wang, Dimitris Papamichail, Steffen Mueller and Steven Skiena.
    Proceedings of the 11th International Meeting on DNA Computing (DNA), 2005.
    Lecture Notes in Computer Science (LNCS), 3892, pages 387-398, 2006.
    [PDF]


28. Web Enabled Robot Design and Dynamic Control Simulation Software Solutions from Task Points Description.
    Tarek M. Sobh, Bei Wang, and Sarosh H. Patel**.
    Proceedings 29th Annual International Conference of the IEEE Industrial Electronics Society (IECON) , 2003.
    [PDF]

Workshop Publications

1. Reeb Space Approximation with Guarantees (Abstract).
   Elizabeth Munch and Bei Wang*.
   25th Annual Fall Workshop on Computational Geometry (FWCG), 2015.
   [PDF] [Proceedings Online]


2. 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.
   [PDF]


3. Interpreting Feature Tracking Through the Lens of Robustness.
   Primoz Skraba and Bei Wang*.
   Topology-Based Methods in Visualization (TopoInVis), 2013.
   [PDF]


4. 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.


5. Kernel Distance for Geometric Inference (Abstract).
   Jeff M. Phillips and Bei Wang*.
   22nd Annual Fall Workshop on Computational Geometry (FWCG), 2012.
   [PDF]


6. Adaptive Sampling with Topological Scores.
   Dan Maljovec, Bei Wang, Ana Kupresanin, Gardard Johannesson, Valerio Pascucci, Peer-Timo Bremer.
   Working with Uncertainty Workshop at IEEE VisWeek, 2011.
   [PDF]


7. Towards Stratification Learning through Homology Inference.
   Paul Bendich, Sayan Mukherjee and Bei Wang*.
   AAAI Fall Symposium on Manifold Learning and its Applications (AAAI), 2010.
   [PDF] [Manifold Learning and its Applications: Papers from the AAAI Fall Symposium]

Manuscripts

1. Visualizing High-Dimensional Data: Advances in the Past Decade.
   Shusen Liu, Dan Maljovec, Bei Wang, Peer-Timo Bremer and Valerio Pascucci.
   Under revision for journal submission, 2016.
   [Survey Website (Maintained by Shusen Liu)]


2. Visual Exploration of Multiway Dependencies for Multivariate Data.
   Hoa Nguyen, Paul Rosen and Bei Wang.
   Under revision, 2015.


3. Topology-Based Active Learning.
   Dan Maljovec, Bei Wang, John Moeller and Valerio Pascucci.
   SCI Technical Report UUSCI-2014-00, 2014.

PhD Thesis

• Separating Features from Noise with Persistence and Statistics.
  Bei Wang.
  Ph.D. Thesis, Duke University, 2010.
  [PDF]