Bei Wang
Data Analysis and Data Visualization




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Bei Wang Phillips
Publish Under: Bei Wang

Assistant Professor, School of Computing
Adjunct Assistant 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

Office Phone: (801) 585-0968 (please do not leave messages)

Research keywords: data visualization, topological data analysis, computational topology, machine learning, and data mining.

CV: PDF (last update July 11, 2019)

Web page last update: May 15, 2020.

Professional Experience

Assistant Professor, School of Computing, University of Utah (2016 - Present)
Faculty Member, Scientific Computing and Imaging (SCI) Institute , University of Utah (2016 - Present)
Adjunct Assistant Professor, Department of Mathematics, University of Utah (2019 - Present)
Research Computer Scientist, Scientific Computing and Imaging Institute (SCI), University of Utah (2011 - 2016)
Postdoctoral Fellow, Scientific Computing and Imaging Institute (SCI), University of Utah (2010 - 2011)
Visiting Researcher, Institute of Science and Technology Austria (IST Austria) (Fall 2009)

Education

Ph.D. in Computer Science, Duke University (2010), Advisor: Herbert Edelsbrunner
Certificate in Computational Biology and Bioinformatics, Duke University (2010)
B.S. in Computer Science and Mathematics, Minor in Psychology, Summa Cum Laude, University of Bridgeport (2003)

Best Paper Awards

Student Awards

Research Interests

I am interested in the analysis and visualization of large and complex data.

My research expertise lies in the theoretical, algorithmic, and application aspects of data analysis and data visualization, with a focus on topological techniques. My research interests include: topological data analysis, data visualization, computational topology, computational geometry, machine learning and data mining. Previously, I have worked on projects related to computational biology and bioinformatics, as well as robotics.

My vision is to tackle problems involving large and complex forms of data that require rich structural descriptions, by combining topological, geometric, statistical, data analysis and visualization techniques.

Current Projects
2019 - 2022
NSF IIS-1910733
Visualizing Robust Features in Vector and Tensor Fields.
Project Website.
2017 - 2020
NSF DBI-1661375
A Scalable Framework for Visual Exploration and Hypotheses Extraction of Phenomics Data using Topological Analytics.

Utah Project Website.
Collaborative Project Website.
Past Projects
2015 - 2019
NSF IIS-1513616
Topological Data Analysis for Large Network Visualization.

Project Web Site.
2016 - 2019
NIH 1R01EB022876
Beyond Diagnostic Classification of Autism.

Project Website.
2016 - 2017
NRAO-NSF Pilot Grant
Feature Extraction & Visualization of ALMA Data Cubes through Topological Data Analysis.

Project Web Site.

Organized Workshops/Tutorials

2020: Visualization in Astrophysics: Developing New Methods, Discovering Our Universe, Educating the Earth at IEEE VIS, October 25-30, 2020.
Organizers: Bei Wang, Juna Kollmeier, Lauren Anderson.

2020: Application Spotlights: Challenges in the Visualization of Bioelectric Fields for Cardiac and Neural Research at IEEE VIS, October 25-30, 2020.
Organizers: Bei Wang, Rob MacLeod, Wilson Good.

2020: Visualization in Astrophysics: Carnegie + SCI Mini-Workshop at SCI, April 27, 2020.
Organizers: Bei Wang, Juna Kollmeier, Lauren Anderson.

2019: 8th Annual Minisymposium on Computational Topology during the Computational Geometry Week, June 18-21, 2019.
Organizers: Bei Wang, Bala Krishnamoorthy, Dmitriy Morozov.

2019: Dagstuhl Seminar: Topology, Computation and Data Analysis, May 19 - 24, 2019.
Organizers: Bei Wang, Michael Kerber, Vijay Natarajan.

2017: Dagstuhl Seminar: Topology, Computation and Data Analysis, July 16 - 21, 2017.
Organizers: Bei Wang, Hamish Carr, Michael Kerber.

2017: 6th Annual Minisymposium on Computational Topology during the Computational Geometry Week, July 4-7, 2017.
Organizers: Bei Wang, Mickael Buchet, Emerson G. Escolar, Clement Maria.

2016: Tutorial: Recent Advancements of Feature-based Flow Visualization and Analysis at IEEE VIS, 2017.
Organizers: Bei Wang, Jun Tao, Hanqi Guo, Tino Weinkauf, Christoph Garth.

2016: Topological Data Analysis in Biomedicine at the 7th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB), Oct 2, 2016.
Organizers: Bei Wang, Bala Krishnamoorthy.

Students

I am looking for talented undergraduate and graduate students who are interested in data analysis and data visualization.
If you are interested and you are a University of Utah student, please email me your CV.
If you are applying to graduate school at School of Computing, University of Utah, please apply through the official admission webpage at http://www.cs.utah.edu/graduate/admissions/.

Current Student

  • Lin Yan (CS PhD, Fall 2017 - present, expected graduation: Spring 2022)
  • Archit Rathore (CS PhD, Summer 2018 - present, expected graduation: Spring 2022)
  • Youjia Zhou (CS PhD, Spring 2019 - present, expected graduation: Spring 2023)
  • Ilkin Safarli (CS PhD, Spring 2020 - present, expected graduation: Spring 2023)
  • Fangfei Lan (CS PhD, Spring 2020 - present, expected graduation: Spring 2024)
  • Michael Young (CS MS Master Thesis, Spring 2020 - present, expected graduation: Spring 2021)
  • Nithin Chalapathi (CS, Undergraduate REU, Spring 2019 - present, expected graduation: Spring 2021)

Past Student

  • Sourabh Palande (CS PhD, Fall 2015 - Summer 2020, graduated Summer 2020), PostDoc @ Michigan State University.
  • Adam Brown (Math PhD, Spring 2017 - Spring 2019, graduated Spring 2019), informal advising, PostDoc @ IST Austria.
  • Yulong Liang (CS MS Master Thesis, Spring 2018 - Spring 2019, graduated Spring 2019), first job @ Microsoft.
  • Yaodong Zhao (CS MS Research Project, Fall 2017 - Spring 2019, graduated Spring 2019), first job @ LeanTaaS.
  • Avani Sharma (CS MS Thesis Project, graduated Spring 2018), first job @ Goldman Sachs.
  • Yiliang Shi (CS, Undergraduate Thesis, graduated Spring 2018), graduate school @ Columbia University.
  • Keri Anderson (CS, Undergraduate Thesis, graduated Spring 2018).
  • William Garnes (CS, Undergraduate REU, graduated Spring 2018), graduate school @ Clemson University.
  • Yixuan (Eric) Wang (MS ECE/CS Master Project, graduated Spring 2017), first Job @ InsideSales, now @ Amazon.

Research Group Alumni (Project Mentoring, Rotation, Independent Study)

Paul Kristoffersen (CS PhD): Independent Study, Spring 2019. Sravan Neerati (CS MS): RA, Fall 2017. Chetal Patil (CS MS): RA, Fall 2017. Tim Sodergren (CS PhD): RA, Fall 2016 - Summer 2017. Vipin Jose (CS MS): RA, Spring 2017. Adam Conkey (CS PhD): Independent Study, Spring 2017. Matt Howa (Undergraduate REU): Spring 2017. Sam Leventhal (CS PhD): Independent Study, Spring 2016. Soumya S. Mishra (CS MS): Independent Study, Fall 2014. Project mentoring as a Research Computer Scientist (2011-2016): Brian Summa (CS PhD), Harsh Bhatia (CS PhD), Yan Zheng (CS PhD), Hoa Nguyen (CS PhD), Wathsala Widanagamaachchi (CS PhD), Dan Maljovec (CS PhD), Shusen Liu (CS PhD), Liang He (CS MS).

Teaching

Upcoming Teaching

Spring 2021: CS 6170 - Computational Topology

Current Teaching

Fall 2020: CS 2100 - Discrete Structures

Past Teaching

Spring 2020: CS 2100 - Discrete Structures

Fall 2019: CS 6965 - Advanced Data Visualization

Spring 2019: CS 6170 - Computational Topology

Fall 2018: On teaching release. Visiting Simons Institute at UC Berkeley: Foundations of Data Science program.

Spring 2018: CS 6965 - Advanced Data Visualization. Award: College of Engineering Top Instructor, Spring 2018.

Fall 2017: CS 2100 - Discrete Structures

Fall 2017: CS 7941 - Data Group Seminar

Spring 2017: CS 6170 - Computational Topology

Fall 2016: CS 6210 - Advanced Scientific Computing I

Fall 2016: CS 7941 - Advanced Data Seminar

Spring 2016: CS 1060 - Explorations in Computer Science

Spring 2016: CS 4960 - Introduction to Computational Geometry

Fall 2015: CS 6210 - Advanced Scientific Computing I

Recent Manuscripts

Papers marked with * use alphabetic ordering of authors.
Students are underlined.
PDF TopoAct: Visually Exploring the Shape of Activations in Deep Learning.
Archit Rathore, Nithin Chalapathi, Sourabh Palande, Bei Wang.
Manuscript under review, 2020.
Supplemental Material.
arXiv:1912.06332.
PDF Gazing Into the Metaboverse: Automated Exploration and Contextualization of Metabolic Data.
Jordan A. Berg, Youjia Zhou, T. Cameron Waller, Yeyun Ouyang, Sara M. Nowinski, Tyler Van Ry, Ian George, James E. Cox, Bei Wang, Jared Rutter.
Manuscript, 2020.
bioRxiv:10.1101/2020.06.25.171850v1.
PDF MVF Designer: Design and Visualization of Morse Vector Fields.
Youjia Zhou, Janis Lazovskis, Michael J. Catanzaro, Matthew Zabka, Bei Wang.
Manuscript in revision, 2019.
arXiv:1912.09580.
PDF Intrinsic Interleaving Distance for Merge Trees.
Ellen Gasparovic, Elizabeth Munch, Steve Oudot, Katharine Turner, Bei Wang, Yusu Wang.
Manuscript, 2019.
arXiv:1908.00063.
PDF Local Versus Global Distances for Zigzag Persistence Modules.
Ellen Gasparovic, Maria Gommel, Emilie Purvine, Radmila Sazdanovic, Bei Wang, Yusu Wang, Lori Ziegelmeier.
Manuscript, 2019.
arXiv:1903.08298.
PDF Mapper on Graphs for Network Visualization.
Mustafa Hajij, Bei Wang, Paul Rosen.
Manuscript, 2018.
arXiv:1804.11242.

Recent Publications

Papers marked with * use alphabetic ordering of authors.
Students are underlined.
2021
PDF 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), accepted, 2021.

2020
PDF 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, accepted, 2020.
DOI: 10.1109/TVCG.2020.3022359
PDF Probabilistic Convergence and Stability of Random Mapper Graphs.
Adam Brown, Omer Bobrowski, Elizabeth Munch, Bei Wang.
Journal of Applied and Computational Topology, in revision, 2020.
arXiv:1909.03488.
PDF 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.
arXiv:1708.08436.
PDF 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
PDF 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

PDF 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.
PDF 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.
PDF Mathematical Foundations in Visualization.
Ingrid Hotz, Roxana Bujack, Christoph Garth, Bei Wang.
In Foundations of Data Visualization, Springer, to appear, 2020
Editors: Min Chen, Helwig Hauser, Penny Rheingans, Gerik Scheuermann.
DOI:10.1007/978-3-030-34444-3
PDF 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
PDF 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

PDF 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
PDF Learning With Topological Features of Functional Brain Networks (Abstract).
Sourabh Palande, Bei Wang.
Algebraic Topology: Methods, Computation, & Science (ATMCS), poster, 2020.

PDF 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.

PDF 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.
PDF 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
PDF 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
PDF 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!

PDF 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!

PDF 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
PDF 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
PDF 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.
PDF 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
PDF 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
PDF 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
PDF 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!
PDF 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
PDF 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
PDF 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
PDF 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
PDF 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
PDF 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
PDF 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
2017
PDF 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
PDF 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.
PDF 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.
AWM-IMA Springer series: Research in Computational Topology, Accepted, 2017.
arXiv:1512.04108.
PDF Robustness for 2D Symmetric Tensor Field Topology.
Bei Wang and Ingrid Hotz.
Modeling, Analysis, and Visualization of Anisotropy, Springer, 2017.

PDF 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
PDF 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
PDF 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
PDF 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.
PDF 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.
Poster presentations at ISBI by Eleanor Wong and at TGDA@OSU by Sourabh Palande.
PDF 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 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 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.
IEEE Transactions on Visualization and Computer Graphics (TVCG), 22(6), pages 1683-1693, 2016.
Supplemental Video. Vortex Video.
Best Paper Award at PacificVis 2016!
PDF 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 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
PDF Reeb Space Approximation with Guarantees (Abstract).
Elizabeth Munch and Bei Wang*.
25th Annual Fall Workshop on Computational Geometry (FWCG), 2015.
Proceedings Online.
PDF 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.
PDF 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.
PDF 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.
PDF 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.
PDFSupplemental Material. Supplemental Video.
PDF 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.
Survey Website.
PDF 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.
PDF 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 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
PDF 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.
PDF 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!
PDF 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.
PDF 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.
PDF 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.
PDF EuroVis Supplemental. EuroVis Video. Journal Online. YouTube.
Software: DataExplorerHD v0.1 (Maintained by Shusen Liu)
PDF 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.
PDF 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.
Proceedings Online.
2013
PDF 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.
Computer Graphics Forum (CGF), 32(2), pages 221-230, 2013.
PDF EuroVis Supplemental. EuroVis Video. CEDMAV Video. Journal Online.
PDF 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.
PDF 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 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 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
PDF 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!
PDF Kernel Distance for Geometric Inference (Abstract).
Jeff M. Phillips and Bei Wang*.
22nd Annual Fall Workshop on Computational Geometry (FWCG), 2012.
PDF 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
PDF 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.
PDF 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
PDF Separating Features from Noise with Persistence and Statistics.
Bei Wang.
Ph.D. Thesis, Duke University, 2010.
PDF 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 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
PDFSpatial 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
PDFTwo 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
PDFA 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
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PDFExperimental 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
PDFWeb 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
PDF 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 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.

Recent Talks

Invited Talk: Topological Thinking in Visualization.
Topological Data Analysis and Related Topics (TDART), AIMR, Tohoku University, 2017.

Invited Talk: Structural Inference of Point Clouds.
Topological Data Analysis and Related Topics (TDART), AIMR, Tohoku University, 2017.

Invited Talk: Topological Data Analysis and Visualization: from Vector Fields to High-Dimensional Data.
Pacific Northwest National Laboratory, 2015.

Invited Talks: Robustness-Based Vector Fields Simplification & Topology-Based Active Learning.
Computer Science Department, Ohio State University, 2014.

Invited Talk: Geometric Inference on Kernel Density Estimates.
SAMSI workshop on Topological Data Analysis, research program on Low Dimensional Structure in High Dimensional Systems, 2014.

Invited Talk: Vector Field Visualization and Simplification based on Robustness.
Computer Science Department Colloquium, University of Connecticut, 2013.

Invited Talk: Topological Data Analysis and Visualization: A Biased and Incomplete Point of View.
Colloquium Series in School of Engineering, University of Bridgeport, 2013.

Invited Talk: PDFHomology and Cohomology in Visualization: From Vector Fields to Memory Reference Traces.
IMA Workshop on Modern Applications of Homology and Cohomology, 2013.

Organizer and Speaker: PDF Topological Data Analysis and Visualization for Large-Scale and High-Dimensional Science Discovery.
PSA Technical Workshop on Topological Data Analysis and Visualization for Large-Scale and High-Dimensional Science Discovery, 2013.

Invited Talk: Geometric Inference on Kernel Density Estimates.
Mini-symposium on Applied and Computational Topology, SIAM Conference on Applied Algebraic Geometry (AG), 2013.

Invited Talk: Stratification Learning through Local Homology Transfer.
AMS-MAA Joint Mathematics Meeting (JMM), special session on Computational and Applied Topology, 2012.

Invited Talk: Towards Stratification Learning through Local Homology Transfer.
Theory Lunch, School of Computer Science, Carnegie Mellon University, 2012.

Seminar Talk: Stratification Learning through Local Homology Transfer.
Applied Math Seminar, Department of mathematics, University of Utah, 2012.

Conference Talk: Stratification Learning.
Yaroslavl international conference Discrete Geometry dedicated to centenary of A.D.Alexandrov, Russia, 2012.

Lecturer: Study of the Elevation function.
Summer school of the Delaunay Laboratory, Russia, 2012.

Invited Talk: Sampling for Local Homology with Vietoris-Rips Complexes.
ACM Symposium on Computational Geometry (SOCG) Workshop on Computational Topology, 2012.

Invited Talk: Stratification Learning through Local Homology Transfer.
Fields Institute for Research in Mathematical Sciences, Thematic Program on Discrete Geometry and Applications, Workshop on Computational Topology, 2011.

Extra

I am always open to discussions on topology, geometry, mathematics, biology, food, and everything in between.
I have a travel blog Jumpy Shell, a travel instagram, and a food blog Bei's Bites, all of which have been more or less inactive because of these kids.
I am married to Jeff M. Phillips, and we have two sons: Stanley, born in 2013, and Max, born in 2015.

I grew up in Chengdu, Sichuan, China.
I came to US after graduating from Chengdu No.7 High School.
My high school celerated its 110 year anniversary in 2015.
Chengdu is a city of gastronomy (as declared by UNESCO in 2011).
It is famous for many things I love, including spicy food, a Giant Sitting Buddha and pandas.