Publications

2024

Pengfei Gu, Zihan Zhao, Hongxiao Wang, Yaopeng Peng, Yizhe Zhang, Nishchal Sapkota, Chaoli Wang, and Danny Z. Chen. Boosting Medical Image Classification with Segmentation Foundation Model. In Proceedings of IEEE International Symposium on Biomedical Imaging, Athens, Greece, May 2024.
[PDF] (417KB)

Kaiyuan Tang and Chaoli Wang. ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasets. In Proceedings of IEEE Pacific Visualization Conference, Tokyo, Japan, Apr 2024.
[PDF] (30.7MB) | [MP4] (53.5MB)

Kaiyuan Tang and Chaoli Wang. STSR-INR: Spatiotemporal Super-Resolution for Multivariate Time-Varying Volumetric Data via Implicit Neural Representation. Computers & Graphics, 119:103874, Apr 2024.
[PDF] (23.2MB) | [MP4] (63.8MB) | [HTM] [Code Available for Download]

Siavash Ghorbany, Ming Hu, Siyuan Yao, Chaoli Wang, Quynh C. Nguyen, Xiaohe Yue, Mitra Alirezaei, Tolga Tasdizen, and Matthew Sisk. Examining the Role of Passive Design Indicators in Energy Burden Reduction: Insights from a Machine Learning and Deep Learning Approach. Building and Environment, 250:111126, Feb 2024.
[HTM]

Xiaojing Duan, Bo Pei, G. Alex Ambrose, Arnon Hershkovitz, Ying Cheng, and Chaoli Wang. Towards Transparent and Trustworthy Prediction of Student Learning Achievement by Including Instructors as Co-Designers: A Case Study. Education and Information Technologies, 29(3):3075-3096, Feb 2024.
[PDF] (2.3MB)

2023

Jun Han and Chaoli Wang. CoordNet: Data Generation and Visualization Generation for Time-Varying Volumes via a Coordinate-Based Neural Network. IEEE Transactions on Visualization and Computer Graphics, 29(12):4951-4963, Dec 2023.
[Presented at IEEE VIS 2023]
[PDF] (40.4MB) | [WMV] (111.8MB) | [HTM] [Code Available for Download]

Pengfei Gu, Danny Z. Chen, and Chaoli Wang. NeRVI: Compressive Neural Representation of Visualization Images for Communicating Volume Visualization Results. Computers & Graphics, 116:216-227, Nov 2023.
[PDF] (17.7MB) | [MP4] (85.5MB) | [HTM] [Code Available for Download]

Zhiyuan Cheng, Zeyuan Li, Zhepeng Luo, Mayleen Liu, Jonathan D’Alonzo, and Chaoli Wang. ArcheryVis: A Tool for Analyzing and Visualizing Archery Performance Data. In Proceedings of International Symposium on Visual Computing, Lake Tahoe, NV, pages 97-108, Oct 2023.
[PDF] (6.0MB)

Chaoli Wang and Jun Han. DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization. IEEE Transactions on Visualization and Computer Graphics, 29(8):3714-3733, Aug 2023.
[Presented at IEEE VIS 2022]
[PDF] (508KB)

Zhichun Guo, Jun Tao, Siming Chen, Nitesh V. Chawla, and Chaoli Wang. SD²: Slicing and Dicing Scholarly Data for Interactive Evaluation of Academic Performance. IEEE Transactions on Visualization and Computer Graphics, 29(8):3569-3585, Aug 2023.
[Presented at IEEE VIS 2022]
[PDF] (7.5MB) | [MP4] (51.2MB) | [HTM] [Code Available for Download]

Siyuan Yao, Jun Han, and Chaoli Wang. GMT: A Deep Learning Approach to Generalized Multivariate Translation for Scientific Data Analysis and Visualization. Computers & Graphics, 112:92-104, May 2023.
[PDF] (29.4MB) | [MP4] (125.1MB) | [HTM] [Code Available for Download]

Yizhe Zhang, Pengfei Gu, Chaoli Wang, and Danny Z. Chen. GrNT: Gate-Regularized Network Training for Improving Multi-Scale Fusion in Medical Image Segmentation. In Proceedings of IEEE International Symposium on Biomedical Imaging, Cartagena, Colombia, 5 pages, Apr 2023.
[PDF] (2.8MB)

Pengfei Gu, Yejia Zhang, Chaoli Wang, and Danny Z. Chen. ConvFormer: Combining CNN and Transformer for Medical Image Segmentation. In Proceedings of IEEE International Symposium on Biomedical Imaging, Cartagena, Colombia, 5 pages, Apr 2023.
[PDF] (1.4MB)

Chase J. Brown, Siyuan Yao, Xiaoyun Zhang, Chad J. Brown, John B. Caven, Krupali U. Krusche, and Chaoli Wang. Visualizing Digital Architectural Data for Heritage Education. In Proceedings of IS&T Conference on Visualization and Data Analysis, San Francisco, CA, pages 393-1-393-7, Jan 2023.
[PDF] (4.5MB) | [MP4] (145.8MB)

2022

Chaoli Wang. VisVisual: A Toolkit for Teaching and Learning Data Visualization. IEEE Computer Graphics and Applications, 42(4):20-26, Jul/Aug 2022.
[Presented at IEEE VIS 2023]
[PDF] (2.6MB) | [HTM] [Project Site]

Brendan J. O’Handley, Yuheng Wu, Haobin Duan, and Chaoli Wang. TreeVisual: Design and Evaluation of a Web-Based Visualization Tool for Teaching and Learning Tree Visualization. In Proceedings of American Society for Engineering Education Annual Conference, Minneapolis, MN, pages 36.509.1-36.509.15, Jun 2022.
[PDF] (2.6MB) | [DEMO] | [HTM] [Code Available for Download]

Jun Han and Chaoli Wang. SurfNet: Learning Surface Representations via Graph Convolutional Network. Computer Graphics Forum (EuroVis 2022), 41(3):109-120, Jun 2022.
[Presented at EuroVis 2022]
[PDF] (69.4MB) | [WMV] (53.8MB) | [HTM] [Code Available for Download]

Jun Han and Chaoli Wang. VCNet: A Generative Model for Volume Completion. Visual Informatics (IEEE PacificVis 2022 Workshop), 6(2):62-73, Jun 2022.
[Presented at IEEE PacificVis 2022]
[PDF] (11.6MB) | [WMV] (46.7MB)

Jun Han and Chaoli Wang. SSR-TVD: Spatial Super-Resolution for Time-Varying Data Analysis and Visualization. IEEE Transactions on Visualization and Computer Graphics, 28(6):2445-2456, Jun 2022.
[Presented at IEEE VIS 2021]
[PDF] (25.8MB) | [WMV] (122.7MB) | [HTM] [Code Available for Download]

Sebastian Weiss, Jun Han, Chaoli Wang, and Rüdiger Westermann. Deep Learning-Based Upscaling for In Situ Volume Visualization. In Hank Childs, Janine Bennett, and Christoph Garth (Eds.) In Situ Visualization for Computational Science, pages 331-352, Springer, May 2022.
[PDF] (12.6MB)

Xiaojing Duan, Chaoli Wang, and Guieswende Rouamba. Designing a Learning Analytics Dashboard to Provide Students with Actionable Feedback and Evaluating Its Impacts. In Proceedings of International Conference on Computer Supported Education, Virtual, volume 2, pages 117-127, Apr 2022.
[PDF] (572KB)

Pengfei Gu, Jun Han, Danny Z. Chen, and Chaoli Wang. Scalar2Vec: Translating Scalar Fields to Vector Fields via Deep Learning. In Proceedings of IEEE Pacific Visualization Symposium, Virtual, pages 31-40, Apr 2022.
[PDF] (14.4MB) | [HTM] [Code Available for Download]

Jun Han and Chaoli Wang. TSR-VFD: Generating Temporal Super-Resolution for Unsteady Vector Field Data. Computers & Graphics, 103:168-179, Apr 2022.
[PDF] (54.9MB) | [HTM] [Code Available for Download]

Reshika P. Velumani, Meng Xia, Jun Han, Chaoli Wang, Alexis K.-H. Lau, and Huamin Qu. AQX: Explaining Air Quality Forecast for Verifying Domain Knowledge Using Feature Importance Visualization. In Proceedings of ACM International Conference on Intelligent User Interfaces, Virtual, pages 720-733, Mar 2022.
[PDF] (2.2MB)

Brendan J. O’Handley, Morgan K. Ludwig, Samantha R. Allison, Michael T. Niemier, Shreya Kumar, Ramzi Bualuan, and Chaoli Wang. CoursePathVis: Course Path Visualization Using Flexible Grouping and Funnel-Augmented Sankey Diagram. In Proceedings of IS&T Conference on Visualization and Data Analysis, Virtual, pages 431-1-431-9, Jan 2022.
[PDF] (3.9MB) | [MP4] (9.9MB) | [DEMO]

Jun Han, Hao Zheng, Danny Z. Chen, and Chaoli Wang. STNet: An End-to-End Generative Framework for Synthesizing Spatiotemporal Super-Resolution Volumes. IEEE Transactions on Visualization and Computer Graphics (IEEE VIS 2021), 28(1):270-280, Jan 2022.
[Presented at IEEE VIS 2021]
[PDF] (22.3MB) | [WMV] (40.2MB) | [HTM] [Code Available for Download]

2021

Pengfei Gu, Jun Han, Danny Z. Chen, and Chaoli Wang. Reconstructing Unsteady Flow Data from Representative Streamlines via Diffusion and Deep Learning Based Denoising. IEEE Computer Graphics and Applications (Special Issue on Powering Visualization with Deep Learning), 41(6):111-121, Nov/Dec 2021.
[IEEE CG&A 2021 Best Paper Award]
[PDF] (12.5MB) | [HTM] [Code Available for Download]

William P. Porter, Conor P. Murphy, Dane R. Williams, Brendan J. O’Handley, and Chaoli Wang. Hierarchical Sankey Diagram: Design and Evaluation. In Proceedings of International Symposium on Visual Computing, Virtual, part II, pages 386-397, Oct 2021.
[PDF] (2.0MB) | [DEMO]

Hao Zheng, Jun Han, Hongxiao Wang, Lin Yang, Zhuo Zhao, Chaoli Wang, and Danny Z. Chen. Hierarchical Self-Supervised Learning for Medical Image Segmentation Based on Multi-Domain Data Aggregation. In Proceedings of International Conference on Medical Image Computing and Computer Assisted Interventions, Virtual, pages 622-632, Sep 2021.
[PDF] (2.4MB)

Pengfei Gu, Hao Zheng, Yizhe Zhang, Chaoli Wang, and Danny Z. Chen. kCBAC-Net: Deeply Supervised Complete Bipartite Networks with Asymmetric Convolutions for Medical Image Segmentation. In Proceedings of International Conference on Medical Image Computing and Computer Assisted Interventions, Virtual, pages 337-347, Sep 2021.
[PDF] (792KB)

Xueyi Bao, Jun Han, and Chaoli Wang. VolumeVisual: Design and Evaluation of an Educational Software Tool for Teaching and Learning Volume Visualization. In Proceedings of American Society for Engineering Education Annual Conference, Virtual, pages 32.259.1-32.259.14, Jul 2021.
[PDF] (1.9MB) | [MP4] (162.9MB) | [DEMO] | [HTM] [Code Available for Download]

Jun Zhang, Jun Tao, Jian-Xun Wang, and Chaoli Wang. SurfRiver: Flattening Stream Surfaces for Comparative Visualization. IEEE Transactions on Visualization and Computer Graphics (IEEE PacificVis 2021), 27(6):2783-2795, Jun 2021.
[Presented at IEEE PacificVis 2021]
[PDF] (15.8MB) | [MP4] (52.3MB)

Jun Han, Hao Zheng, Yunhao Xing, Danny Z. Chen, and Chaoli Wang. V2V: A Deep Learning Approach to Variable-to-Variable Selection and Translation for Multivariate Time-Varying Data. IEEE Transactions on Visualization and Computer Graphics (IEEE SciVis 2020), 27(2):1290-1300, Feb 2021.
[Presented at IEEE VIS 2020]
[PDF] (26.4MB) | [WMV] (66.5MB) | [HTM] [Code Available for Download]

2020

Yucheng Huang, Lei Shi, Yue Su, Yifan Hu, Hanghang Tong, Chaoli Wang, Tong Yang, Deyun Wang, and Shuo Liang. Eiffel: Evolutionary Flow Map for Influence Graph Visualization. IEEE Transactions on Visualization and Computer Graphics, 26(10):2944-2960, Oct 2020.
[Presented at IEEE VIS 2019]
[PDF] (11.3MB) | [MP4] (50.7MB)

Hao Zheng, Susan M. Motch Perrine, M. Kathleen Pitirri, Kazuhiko Kawasaki, Chaoli Wang, Joan T. Richtsmeier, and Danny Z. Chen. Cartilage Segmentation in High-Resolution 3D Micro-CT Images via Uncertainty-Guided Self-Training with Very Sparse Annotation. In Proceedings of International Conference on Medical Image Computing and Computer Assisted Interventions, Virtual, pages 802-812, Oct 2020.
[PDF] (1.9MB)

Chaoli Wang. Visualization Laboratory at University of Notre Dame. Visual Informatics, 4(3):63-68, Sep 2020.
[PDF] (2.1MB)

Jia Yan, Lei Shi, Jun Tao, Xiaolong Yu, Zhou Zhuang, Congcong Huang, Rulei Yu, Purui Su, Chaoli Wang, and Yang Chen. Visual Analysis of Collective Anomalies Using Faceted High-Order Correlation Graphs. IEEE Transactions on Visualization and Computer Graphics, 26(7):2517-2534, Jul 2020.
[PDF] (6.0MB) | [MP4] (39.4MB)

Martin Imre, Wenqing Chang, Shuzhan Wang, Christine P. Trinter, and Chaoli Wang. GraphVisual: Design and Evaluation of a Web-Based Visualization Tool for Teaching and Learning Graph Visualization. In Proceedings of American Society for Engineering Education Annual Conference, Virtual, pages 28.501.1-28.501.15, Jun 2020.
[PDF] (1.9MB) | [DEMO] | [HTM] [Code Available for Download]

Li Guo, Shaojie Ye, Jun Han, Hao Zheng, Han Gao, Danny Z. Chen, Jian-Xun Wang, and Chaoli Wang. SSR-VFD: Spatial Super-Resolution for Vector Field Data Analysis and Visualization. In Proceedings of IEEE Pacific Visualization Symposium, Virtual, pages 71-80, Jun 2020.
[PDF] (70.1MB) | [HTM] [Code Available for Download]

Martin Imre, Jun Tao, Yongyu Wang, Zhiqiang Zhao, Zhuo Feng, and Chaoli Wang. Spectrum-Preserving Sparsification for Visualization of Big Graphs. Computers & Graphics, 87:89-102, Apr 2020.
[Presented at EuroVis 2021]
[PDF] (7.5MB)

Jun Han, Jun Tao, and Chaoli Wang. FlowNet: A Deep Learning Framework for Clustering and Selection of Streamlines and Stream Surfaces. IEEE Transactions on Visualization and Computer Graphics, 26(4):1732-1744, Apr 2020.
[Presented at IEEE VIS 2019]
[PDF] (13.8MB) | [WMV] (67.8MB) | [PPTX] (82.3MB) | [HTM] [Code and Training Data Available for Download]

Xiaojing Duan, G. Alex Ambrose, Chaoli Wang, Kevin Abbott, Victoria Woodard, and Catlin Schalk. PerformanceVis: Homework & Exam Analytics Dashboard for Inclusive Student Success. In Companion Proceedings of International Conference on Learning Analytics & Knowledge, Virtual, Mar 2020.
[PDF] (341KB) | [Y2U]

Tianxiao Hu, Hao Zheng, Chen Liang, Sirou Zhu, Natalie Imirzian, Yizhe Zhang, Chaoli Wang, Danny Z. Chen, and David P. Hughes. AntVis: A Web-Based Visual Analytics Tool for Exploring Ant Movement Data. Visual Informatics, 4(1):58-70, Mar 2020.
[PDF] (3.1MB) | [DEMO]

Lei Shi, Qi Liao, Hanghang Tong, Yifan Hu, Chaoli Wang, Chuang Lin, and Weihong Qian. OnionGraph: Hierarchical Topology+Attribute Multivariate Network Visualization. Visual Informatics, 4(1):43-57, Mar 2020.
[PDF] (3.2MB)

Hao Zheng, Yizhe Zhang, Lin Yang, Chaoli Wang, and Danny Z. Chen. An Annotation Sparsification Strategy for 3D Medical Image Segmentation via Representative Selection and Self-Training. In Proceedings of AAAI Conference on Artificial Intelligence, New York, NY, pages 6925-6932, Feb 2020.
[PDF] (1.9MB)

Jun Han and Chaoli Wang. TSR-TVD: Temporal Super-Resolution for Time-Varying Data Analysis and Visualization. IEEE Transactions on Visualization and Computer Graphics (IEEE SciVis 2019), 26(1):205-215, Jan 2020.
[Presented at IEEE VIS 2019]
[PDF] (53.0MB) | [WMV] (58.1MB) | [PPTX] (127.2MB) | [HTM] [Code Available for Download]

2019

Haozhang Deng, Xuemeng Wang, Zhiyi Guo, Ashley Decker, Xiaojing Duan, Chaoli Wang, G. Alex Ambrose, and Kevin Abbott. PerformanceVis: Visual Analytics of Student Performance Data from an Introductory Chemistry Course. Visual Informatics, 3(4):166-176, Dec 2019.
[PDF] (2.5MB) | [DEMO]

Kecheng Lu, Chaoli Wang, Keqin Wu, Minglun Gong, and Yunhai Wang. A Unified Framework for Exploring Time-Varying Volumetric Data Based on Block Correspondence. Visual Informatics, 3(4):166-176, Dec 2019.
[PDF] (1.6MB)

Jun Ma, Jun Tao, Chaoli Wang, Can Li, Ching-Kuang Shene, and Seung Hyun Kim. Moving with the Flow: An Automatic Tour of Unsteady Flow Fields. Journal of Visualization (ChinaVis 2019), 22(6):1125-1144, Dec 2019.
[Presented at ChinaVis 2019]
[PDF] (5.3MB) | [WMV] (96.2MB zipped) | [PPTX] (35.6MB)

William P. Porter, Yunhao Xing, Blaise R. von Ohlen, Jun Han, and Chaoli Wang. A Deep Learning Approach to Selecting Representative Time Steps for Time-Varying Multivariate Data. In Proceedings of IEEE VIS Conference (Short Papers), Vancouver, Canada, pages 131-135, Oct 2019.
[PDF] (12.4MB) | [PPTX] (40.0MB)

Hao Zheng, Lin Yang, Jun Han, Yizhe Zhang, Peixian Liang, Zhuo Zhao, Chaoli Wang, and Danny Z. Chen. HFA-Net: 3D Cardiovascular Image Segmentation with Asymmetrical Pooling and Content-Aware Fusion. In Proceedings of International Conference on Medical Image Computing and Computer Assisted Interventions, Shenzhen, China, pages 759-767, Oct 2019.
[PDF] (1.2MB)

Martin Imre, Jun Han, Julien Dominski, Michael Churchill, Ralph Kube, Choong-Seock Chang, Tom Peterka, Hanqi Guo, and Chaoli Wang. ContourNet: Salient Local Contour Identification for Blob Detection in Plasma Fusion Simulation Data. In Proceedings of International Symposium on Visual Computing, Lake Tahoe, NV, part I, pages 289-301, Oct 2019.
[PDF] (1.5MB) | [HTM] [Code Available for Download]

Jun Han, Jun Tao, Hao Zheng, Hanqi Guo, Danny Z. Chen, and Chaoli Wang. Flow Field Reduction via Reconstructing Vector Data from 3D Streamlines Using Deep Learning. IEEE Computer Graphics and Applications (Special Issue on Deep Learning in Visualization and Image Processing), 39(4):54-67, Jul/Aug 2019.
[Presented at IEEE VIS 2020]
[PDF] (5.9MB) | [HTM] [Code and Training Data Available for Download]

Hao Zheng, Yizhe Zhang, Lin Yang, Peixian Liang, Zhuo Zhao, Chaoli Wang, and Danny Z. Chen. A New Ensemble Learning Framework for 3D Biomedical Image Segmentation. In Proceedings of AAAI Conference on Artificial Intelligence, Honolulu, HI, pages 5909-5916, Jan 2019.
[Oral Presentation]
[PDF] (515KB)

Hao Zheng, Lin Yang, Jianxu Chen, Jun Han, Yizhe Zhang, Peixian Liang, Zhuo Zhao, Chaoli Wang, and Danny Z. Chen. Biomedical Image Segmentation via Representative Annotation. In Proceedings of AAAI Conference on Artificial Intelligence, Honolulu, HI, pages 5901-5908, Jan 2019.
[Oral Presentation]
[PDF] (1.3MB)

Maggie C. Goulden, Eric Gronda, Yurou Yang, Zihang Zhang, Jun Tao, Chaoli Wang, Xiaojing Duan, G. Alex Ambrose, Kevin Abbott, and Patrick Miller. CCVis: Visual Analytics of Student Online Learning Behaviors Using Course Clickstream Data. In Proceedings of IS&T Conference on Visualization and Data Analysis, Burlingame, CA, pages 681-1-681-12, Jan 2019.
[Outstanding Paper Award]
[PDF] (2.2MB) | [PPTX] (680KB) | [DEMO]

Jun Tao, Martin Imre, Chaoli Wang, Nitesh V. Chawla, Hanqi Guo, Gökhan Sever, and Seung Hyun Kim. Exploring Time-Varying Multivariate Volume Data Using Matrix of Isosurface Similarity Maps. IEEE Transactions on Visualization and Computer Graphics (IEEE SciVis 2018), 25(1):1236-1245, Jan 2019.
[Presented at IEEE VIS 2018]
[PDF] (7.3MB) | [WMV] (75.3MB) | [PPTX] (130.6MB)

2018

Jun Tao, Chaoli Wang, Nitesh V. Chawla, Lei Shi, and Seung Hyun Kim. Semantic Flow Graph: A Framework for Discovering Object Relationships in Flow Fields. IEEE Transactions on Visualization and Computer Graphics, 24(12):3200-3213, Dec 2018.
[Presented at IEEE VIS 2018]
[PDF] (2.8MB) | [WMV] (92.1MB) | [PPTX] (46.3MB)

Chaoli Wang. Deep Learning Meets Flow Visualization. Big Data Challenges for Predictive Modeling of Complex Systems Symposium, Hong Kong, China, Nov 2018.
[PDF] (400KB)

Jun Tao and Chaoli Wang. Semi-Automatic Generation of Stream Surfaces via Sketching. IEEE Transactions on Visualization and Computer Graphics, 24(9):2622-2635, Sep 2018.
[PDF] (4.7MB) | [WMV] (45.6MB)

Martin Imre, Jun Tao, and Chaoli Wang. Identifying Nearly Equally Spaced Isosurfaces for Volumetric Data Sets. Computers & Graphics, 72:82-97, May 2018.
[PDF] (3.7MB) | [HTM] [Code Available for Download]

Jun Tao, Lei Shi, Zhou Zhuang, Congcong Huang, Rulei Yu, Purui Su, Chaoli Wang, and Yang Chen. Visual Analysis of Collective Anomalies Through High-Order Correlation Graph. In Proceedings of IEEE Pacific Visualization Symposium, Kobe, Japan, pages 150-159, Apr 2018.
[PDF] (1.9MB) | [MP4] (35.0MB)

Samuel M. Bailey, Justin A. Wei, Chaoli Wang, Denis Parra, and Peter Brusilovsky. CNVis: A Web-Based Visual Analytics Tool for Exploring Conference Navigator Data. In Proceedings of IS&T Conference on Visualization and Data Analysis, Burlingame, CA, pages 376-1-376-11, Jan 2018.
[PDF] (2.0MB) | [DEMO]

Chaoli Wang. Graph-Based Techniques for Visual Analytics of Scientific Data Sets. IEEE Computing in Science & Engineering, 20(1):93-103, Jan/Feb 2018.
[PDF] (2.6MB)

2017

Man Wang, Jean Mayo, Ching-Kuang Shene, Steven M. Carr, and Chaoli Wang. UNIXvisual: A Visualization Tool for Teaching UNIX Permissions. In Proceedings of ACM Conference on Innovation and Technology in Computer Science Education, Bologna, Italy, pages 194-199, Jul 2017.
[PDF] (921KB) | [HTM]

Jian Xu, Jun Tao, Nitesh V. Chawla, and Chaoli Wang. Demo Abstract: Visual Analytics of Higher-Order Dependencies in Sensor Data. In Proceedings of ACM/IEEE International Conference on Internet-of-Things Design and Implementation, Pittsburgh, PA, pages 297-298, Apr 2017.
[PDF] (651KB)

Martin Imre, Jun Tao, and Chaoli Wang. Efficient GPU-Accelerated Computation of Isosurface Similarity Maps. In Proceedings of IEEE Pacific Visualization Symposium (Visualization Notes), Seoul, Korea, pages 180-184, Apr 2017.
[PDF] (1.0MB) | [HTM] [Code Available for Download]

Jun Tao, Jian Xu, Chaoli Wang, and Nitesh V. Chawla. HoNVis: Visualizing and Exploring Higher-Order Networks. In Proceedings of IEEE Pacific Visualization Symposium, Seoul, Korea, pages 1-10, Apr 2017.
[PDF] (1.6MB) | [MP4] (26.9MB) | [PPTX] (140.7MB) | [HTM]

Yi Gu, Chaoli Wang, Robert Bixler, and Sidney D’Mello. ETGraph: A Graph-Based Approach for Visual Analytics of Eye-Tracking Data. Computers & Graphics, 62:1-14, Feb 2017.
[PDF] (4.2MB) | [WMV] (36.6MB)

Chaoli Wang and Jun Tao. Graphs in Scientific Visualization: A Survey. Computer Graphics Forum, 36(1):263-287, Jan 2017.
[PDF] (3.6MB)

Yi Gu, Chaoli Wang, Jun Ma, Robert J. Nemiroff, David L. Kao, and Denis Parra. Visualization and Recommendation of Large Image and Text Collections toward Effective Sensemaking. Information Visualization, 16(1):21-47, Jan 2017.
[PDF] (8.9MB) | [WMV] (42.5MB)

2016

Jun Tao and Chaoli Wang. Peeling the Flow: A Sketch-Based Interface to Generate Stream Surfaces. In Proceedings of ACM SIGGRAPH Asia Symposium on Visualization, Macao, China, pages 14-1-14-8, Dec 2016.
[PDF] (1.9MB) | [MP4] (65.8MB)

Ian Turk, Matthew Sinda, Xin’an Zhou, Jun Tao, Chaoli Wang, and Qi Liao. Exploration of Linked Anomalies in Sensor Data for Suspicious Behavior Detection. International Journal of Software and Informatics, 10(3), 10 pages, Oct 2016.
[PDF] (947KB) | [WMV] (15.4MB)

Jun Tao, Chaoli Wang, Nitesh V. Chawla, and Lei Shi. Semantic Flow Graph: A Framework to Explore 3D Flow Fields. IEEE VIS Poster, Baltimore, MD, Oct 2016.
[PDF] (1.4MB) | [WMV] (15.6MB)

Jun Tao, Xiaoke Huang, Feng Qiu, Chaoli Wang, Jingfeng Jiang, Ching-Kuang Shene, Ye Zhao, and Daphne Yu. VesselMap: A Web Interface to Explore Multivariate Vascular Data. Computers & Graphics, 59:79-92, Oct 2016.
[PDF] (2.8MB) | [WMV] (18.7MB)

Jun Ma, Jun Tao, Melissa Keranen, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang. AESvisual: A Visualization Tool for the AES Cipher. In Proceedings of ACM Conference on Innovation and Technology in Computer Science Education, Arequipa, Peru, page 230-235, Jul 2016.
[PDF] (2.0MB)

Man Wang, Jean Mayo, Ching-Kuang Shene, Steven M. Carr, and Chaoli Wang. UNIXvisual: A Visualization Tool for Teaching the UNIX Permission Model. In Proceedings of ACM Conference on Innovation and Technology in Computer Science Education (Poster). Arequipa, Peru, page 356, Jul 2016.
[PDF] (151KB)

Jun Tao, Chaoli Wang, Ching-Kuang Shene, and Raymond A. Shaw. A Vocabulary Approach to Partial Streamline Matching and Exploratory Flow Visualization. IEEE Transactions on Visualization and Computer Graphics, 22(5):1503-1516, May 2016.
[PDF] (3.5MB) | [WMV] (45.6MB) | [HTM] [Library Available for Download]

Man Wang, Jun Tao, Jun Ma, Yang Shen, and Chaoli Wang. FlowVisual: A Visualization App for Teaching and Understanding 3D Flow Field Concepts. In Proceedings of IS&T Conference on Visualization and Data Analysis, San Francisco, CA, pages 476-1-476-10, Feb 2016.
[PDF] (2.0MB) | [MP4] (81.1MB) | [HTM] [App Available for Download]

Yi Gu, Chaoli Wang, Tom Peterka, Robert Jacob, and Seung Hyun Kim. Mining Graphs for Understanding Time-Varying Volumetric Data. IEEE Transactions on Visualization and Computer Graphics (IEEE SciVis 2015), 22(1):965-974, Jan 2016.
[Presented at IEEE VIS 2015]
[PDF] (3.1MB) | [WMV] (16.8MB) | [HTM] [Code Available for Download]

2015

Yifei Li, Chaoli Wang, and Ching-Kuang Shene. Extracting Flow Features via Supervised Streamline Segmentation. Computers & Graphics, 52:79-92, Nov 2015.
[PDF] (5.3MB) | [MP4] (6.1MB) | [HTM] [Code Available for Download]

Man Wang, Jean Mayo, Ching-Kuang Shene, Thomas Lake, Steven M. Carr, and Chaoli Wang. RBACvisual: A Visualization Tool for Teaching Access Control Using Role-Based Access Control. In Proceedings of ACM Conference on Innovation and Technology in Computer Science Education, Vilnius, Lithuania, pages 141-146, Jul 2015.
[PDF] (864KB) | [HTM]

Can Li, Jun Ma, Jun Tao, Jean Mayo, Ching-Kuang Shene, Melissa Keranen, and Chaoli Wang. VIGvisual: A Visualization Tool for the Vigenère Cipher. In Proceedings of ACM Conference on Innovation and Technology in Computer Science Education, Vilnius, Lithuania, pages 129-134, Jul 2015.
[PDF] (615KB)

Yachen Tang, Chee-Wooi Ten, Chaoli Wang, and Gordon Parker. Extraction of Energy Information from Analog Meters Using Image Processing. IEEE Transactions on Smart Grid, 6(4):2032-2040, Jul 2015.
[PDF] (2.3MB)

Chaoli Wang, John P. Reese, Huan Zhang, Jun Tao, Yi Gu, Jun Ma, and Robert J. Nemiroff. Similarity-Based Visualization of Large Image Collections. Information Visualization, 14(3):183-203, Jul 2015.
[PDF] (6.9MB)

Jun Ma, Jun Tao, Melissa Keranen, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang. SHAvisual: A Visualization Tool for Secure Hash Algorithm. In Proceedings of American Society for Engineering Education Annual Conference, Seattle, WA, pages 26.1371.1-26.1371.18, Jun 2015.
[PDF] (1.2MB)

Chaoli Wang. A Survey of Graph-Based Representations and Techniques for Scientific Visualization. Eurographics Conference on Visualization – State of The Art Reports, Cagliari, Italy, pages 41-60, May 2015.
[PDF] (3.0MB) | [PPTX] (34.8MB)

Yi Gu, Chaoli Wang, Jun Ma, Robert J. Nemiroff, and David L. Kao. iGraph: A Graph-Based Technique for Visual Analytics of Image and Text Collections. In Proceedings of IS&T/SPIE Conference on Visualization and Data Analysis, San Francisco, CA, pages 939708-1-939708-15, Feb 2015.
[Best Paper Award]
[PDF] (5.2MB) | [WMV] (62.3MB)

2014

Jun Ma, Chaoli Wang, Ching-Kuang Shene, and Jingfeng Jiang. A Graph-Based Interface for Visual Analytics of 3D Streamlines and Pathlines. IEEE Transactions on Visualization and Computer Graphics, 20(8):1127-1140, Aug 2014.
[PDF] (4.2MB) | [WMV] (45.1MB)

Man Wang, Steven M. Carr, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang. MLSvisual: A Visualization Tool for Teaching Access Control Using Multi-Level Security. In Proceedings of ACM Conference on Innovation and Technology in Computer Science Education, Uppsala, Sweden, pages 93-98, Jun 2014.
[PDF] (1.2MB) | [HTM]

Jun Ma, Jun Tao, Melissa Keranen, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang. SHAvisual: A Secure Hash Algorithm Visualization Tool. In Proceedings of ACM Conference on Innovation and Technology in Computer Science Education (Poster), Uppsala, Sweden, page 338, Jun 2014.
[PDF] (53KB)

Yi Gu, Nilufer Onder, Ching-Kuang Shene, and Chaoli Wang. FPAvisual: A Tool for Visualizing the Effects of Floating-Point Finite-Precision Arithmetic. In Proceedings of American Society for Engineering Education Annual Conference, Indianapolis, IN, pages 24.627.1-24.627.19, Jun 2014.
[PDF] (1.2MB) | [MP4] (37.6MB)

Jun Tao, Jun Ma, Melissa Keranen, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang. RSAvisual: A Visualization Tool for the RSA Cipher. In Proceedings of ACM Technical Symposium on Computer Science Education, Atlanta, GA, pages 635-640, Mar 2014.
[PDF] (627KB)

Jun Ma, James Walker, Chaoli Wang, Scott A. Kuhl, and Ching-Kuang Shene. FlowTour: An Automatic Guide for Exploring Internal Flow Features. In Proceedings of IEEE Pacific Visualization Symposium, Yokohama, Japan, pages 25-32, Mar 2014.
[PDF] (3.5MB) | [WMV] (37.7MB) | [PPTX] (142.5MB)

Jun Tao, Chaoli Wang, and Ching-Kuang Shene. FlowString: Partial Streamline Matching Using Shape Invariant Similarity Measure for Exploratory Flow Visualization. In Proceedings of IEEE Pacific Visualization Symposium, Yokohama, Japan, pages 9-16, Mar 2014.
[PDF] (2.5MB) | [WMV] (31.6MB) | [PPTX] (100.9MB) | [HTM] [Library Available for Download]

Yifei Li, Chaoli Wang, and Ching-Kuang Shene. Streamline Similarity Analysis Using Bag-of-Features. In Proceedings of IS&T/SPIE Conference on Visualization and Data Analysis, San Francisco, CA, pages 90170N-1-90170N-12, Feb 2014.
[PDF] (2.7MB)

Jun Tao, Chaoli Wang, Ching-Kuang Shene, and Seung Hyun Kim. A Deformation Framework for Focus+Context Flow Visualization. IEEE Transactions on Visualization and Computer Graphics, 20(1):42-55, Jan 2014.
[Presented at IEEE VIS 2014]
[PDF] (12.2MB) | [WMV] (32.4MB) | [PPTX] (78.1MB)

2013

James Walker, Jun Ma, Scott A. Kuhl, and Chaoli Wang. An Evaluation of Flow Field Visualization with Internal Views. In Proceedings of ACM Symposium on Applied Perception (Poster), Dublin, Ireland, page 116, Aug 2013.
[PDF] (402KB)

Man Wang, Jun Tao, Chaoli Wang, Ching-Kuang Shene, and Seung Hyun Kim. FlowVisual: Design and Evaluation of a Visualization Tool for Teaching 2D Flow Field Concepts. In Proceedings of American Society for Engineering Education Annual Conference, Atlanta, GA, pages 23.609.1-23.609.20, Jun 2013.
[PDF] (3.0MB) | [WMV] (24.3MB) | [HTM] [Software Available for Download]

Huan Zhang, Jun Tao, Fang Ruan, and Chaoli Wang. A Study of Animated Transition in Similarity-Based Tiled Image Layout. Tsinghua Science and Technology (Special Issue on Visualization and Computer Graphics), 18(2):157-170, Apr 2013.
[PDF] (3.8MB) | [WMV] (33.5MB)

Jun Tao, Jun Ma, Chaoli Wang, and Ching-Kuang Shene. A Unified Approach to Streamline Selection and Viewpoint Selection for 3D Flow Visualization. IEEE Transactions on Visualization and Computer Graphics, 19(3):393-406, Mar 2013.
[PDF] (7.1MB) | [AVI] (32.8MB)

Jun Ma, Chaoli Wang, and Ching-Kuang Shene. FlowGraph: A Compound Hierarchical Graph for Flow Field Exploration. In Proceedings of IEEE Pacific Visualization Symposium, Sydney, Australia, pages 233-240, Feb 2013.
[Honorable Mention Award]
[PDF] (2.5MB) | [WMV] (37.6MB) | [PPTX] (85.6MB)

Yi Gu and Chaoli Wang. iTree: Exploring Time-Varying Data Using Indexable Tree. In Proceedings of IEEE Pacific Visualization Symposium, Sydney, Australia, pages 137-144, Feb 2013.
[PDF] (2.0MB) | [WMV] (40.1MB) | [PPTX] (78.8MB)

Chaoli Wang, John P. Reese, Huan Zhang, Jun Tao, and Robert J. Nemiroff. iMap: A Stable Layout for Navigating Large Image Collections with Embedded Search. In Proceedings of IS&T/SPIE Conference on Visualization and Data Analysis, Burlingame, CA, pages 86540K-1-86540K-14, Feb 2013.
[Best Paper Award]
[PDF] (4.1MB) | [WMV] (34.8MB) | [PPTX] (46.3MB)

Jun Ma, Chaoli Wang, and Ching-Kuang Shene. Coherent View-Dependent Streamline Selection for Importance-Driven Flow Visualization. In Proceedings of IS&T/SPIE Conference on Visualization and Data Analysis, Burlingame, CA, pages 865407-1-865407-15, Feb 2013.
[PDF] (7.5MB) | [WMV] (17.3MB) | [PPTX] (18.0MB)

2012

Yifei Li, Steven M. Carr, Jean Mayo, Ching-Kuang Shene, and Chaoli Wang. DTEvisual: A Visualization System for Teaching Access Control Using Domain Type Enforcement. The Journal of Computing Sciences in Colleges, 28(1):125-132, Oct 2012.
[PDF] (202KB) | [HTM]

Hongfeng Yu, Chaoli Wang, Ching-Kuang Shene, and Jacqueline H. Chen. Hierarchical Streamline Bundles. IEEE Transactions on Visualization and Computer Graphics, 18(8):1353-1367, Aug 2012.
[Presented at IEEE VisWeek 2012]
[PDF] (5.3MB) | [WMV] (89.5MB)

Kun-Chuan Feng, Chaoli Wang, Han-Wei Shen, and Tong-Yee Lee. Coherent Time-Varying Graph Drawing with Multifocus+Context Interaction. IEEE Transactions on Visualization and Computer Graphics, 18(8):1330-1342, Aug 2012.
[Presented at IEEE VisWeek 2012]
[PDF] (5.3MB) | [PPTX] (54.5MB) | [HTM]

2011

Yi Gu and Chaoli Wang. TransGraph: Hierarchical Exploration of Transition Relationships in Time-Varying Volumetric Data. IEEE Transactions on Visualization and Computer Graphics (IEEE Vis 2011), 17(12):2015-2024, Dec 2011.
[Presented at IEEE VisWeek 2011]
[PDF] (2.4MB) | [WMV] (31.5MB)

Jun Ma, Jun Tao, Chaoli Wang, and Ching-Kuang Shene. Streamline Selection and Viewpoint Selection via Information Channel. IEEE VisWeek Poster, Providence, RI, Oct 2011.
[PDF] (1.3MB)

Chaoli Wang, Hongfeng Yu, Ray W. Grout, Kwan-Liu Ma, and Jacqueline H. Chen. Analyzing Information Transfer in Time-Varying Multivariate Data. In Proceedings of IEEE Pacific Visualization Symposium, Hong Kong, China, pages 99-106, Mar 2011.
[Cover Image]
[PDF] (2.1MB) | [WMV] (38.5MB)

Cheng-Kai Chen, Chaoli Wang, Kwan-Liu Ma, and Andrew T. Wittenberg. Static Correlation Visualization for Large Time-Varying Volume Data. In Proceedings of IEEE Pacific Visualization Symposium, Hong Kong, China, pages 27-34, Mar 2011.
[Cover Image]
[PDF] (4.3MB) | [MP4] (18.0MB)

Yu-Shuen Wang, Chaoli Wang, Tong-Yee Lee, and Kwan-Liu Ma. Feature-Preserving Volume Data Reduction and Focus+Context Visualization. IEEE Transactions on Visualization and Computer Graphics, 17(2):171-181, Feb 2011.
[PDF] (5.7MB) | [MP4] (42.9MB)

Chaoli Wang and Han-Wei Shen. Information Theory in Scientific Visualization. Entropy (Special Issue on Advances in Information Theory), 13(1):254-273, Jan 2011.
[PDF] (811KB)

2010

Yi Gu and Chaoli Wang. A Study of Hierarchical Correlation Clustering for Scientific Volume Data. In Proceedings of International Symposium on Visual Computing, Las Vegas, NV, part III, pages 437-446, Nov 2010.
[PDF] (1.6MB)

Hongfeng Yu, Chaoli Wang, Ching-Kuang Shene, and Jacqueline H. Chen. Hierarchical Streamline Bundles for Visualizing 2D Flow Fields. IEEE VisWeek Poster, Salt Lake City, UT, Oct 2010.
[PDF] (811KB) | [WMV] (7.8MB)

Hiroshi Akiba, Chaoli Wang, and Kwan-Liu Ma. AniViz: A Template-Based Animation Tool for Volume Visualization. IEEE Computer Graphics and Applications, 30(5):61-71, Sep/Oct 2010.
[PDF] (7.4MB) | [MOV] (72.7MB)

Hongfeng Yu, Chaoli Wang, Ray W. Grout, Jacqueline H. Chen, and Kwan-Liu Ma. In Situ Visualization for Large-Scale Combustion Simulations. IEEE Computer Graphics and Applications, 30(3):45-57, May/Jun 2010.
[PDF] (5.7MB)

Jishang Wei, Chaoli Wang, Hongfeng Yu, and Kwan-Liu Ma. A Sketch-Based Interface for Classifying and Visualizing Vector Fields. In Proceedings of IEEE Pacific Visualization Symposium, Taipei, Taiwan, pages 129-136, Mar 2010.
[PDF] (3.4MB) | [WMV] (10.4MB)

Chaoli Wang, Hongfeng Yu, and Kwan-Liu Ma. Application-Driven Compression for Visualizing Large-Scale Time-Varying Data. IEEE Computer Graphics and Applications, 30(1):59-69, Jan/Feb 2010.
[PDF] (7.4MB) | [WMV] (25.2MB)

2009

Jeffrey Sukharev, Chaoli Wang, Kwan-Liu Ma, and Andrew T. Wittenberg. Correlation Study of Time-Varying Multivariate Climate Data Sets. In Proceedings of IEEE Pacific Visualization Symposium, Beijing, China, pages 161-168, Apr 2009.
[Cover Image]
[PDF] (3.3MB) | [WMV] (13.1MB)

Kwan-Liu Ma, Chaoli Wang, Hongfeng Yu, Kenneth Moreland, Jian Huang, and Robert Ross. Next-Generation Visualization Technologies: Enabling Discoveries at Extreme Scale. SciDAC Review, 12:12-21, Spring 2009.
[PDF] (1.6MB)

2008

Hongfeng Yu, Chaoli Wang, and Kwan-Liu Ma. Massively Parallel Volume Rendering Using 2-3 Swap Image Compositing. In Proceedings of ACM/IEEE Supercomputing Conference, Austin, TX, pages 48-1-48-11, Nov 2008.
[PDF] (1.7MB)

Chaoli Wang and Kwan-Liu Ma. Information and Knowledge Assisted Analysis and Visualization of Large-Scale Data. In Proceedings of ACM/IEEE Supercomputing Ultrascale Visualization Workshop, Austin, TX, pages 1-8, Nov 2008.
[PDF] (1.5MB)

Chaoli Wang, Hongfeng Yu, and Kwan-Liu Ma. Importance-Driven Time-Varying Data Visualization. IEEE Transactions on Visualization and Computer Graphics (IEEE Vis 2008), 14(6):1547-1554, Nov/Dec 2008.
[Cover Image] [Presented at IEEE VisWeek 2008]
[PDF] (2.9MB) | [WMV] (30.3MB) | [PPT] (9.6MB)

Jeffrey Sukharev, Chaoli Wang, and Kwan-Liu Ma. Statistical Analysis and Visualization of Time-Varying Multivariate Climate Data Sets. IEEE Visualization Knowledge-Assisted Visualization Workshop, Columbus, OH, Oct 2008.
[PDF] (394KB)

Kwan-Liu Ma and Chaoli Wang. Social-Aware Collaborative Visualization for Large Scientific Projects. In Proceedings of International Symposium on Collaborative Technologies and Systems, Irvine, CA, pages 190-195, May 2008.
[PDF] (356KB) | [PPT] (3.0MB)

Chaoli Wang and Kwan-Liu Ma. A Statistical Approach to Volume Data Quality Assessment. IEEE Transactions on Visualization and Computer Graphics, 14(3):590-602, May/Jun 2008.
[Cover Image]
[PDF] (3.2MB)

2007

Hongfeng Yu, Chaoli Wang, and Kwan-Liu Ma. Parallel Hierarchical Visualization of Large Time-Varying 3D Vector Fields. In Proceedings of ACM/IEEE Supercomputing Conference, Reno, NV, pages 24-1-24-12, Nov 2007.
[PDF] (4.2MB)

Chaoli Wang, Hongfeng Yu, and Kwan-Liu Ma. Knowledge-Assisted Visualization of Turbulent Combustion Simulations. IEEE Visualization Knowledge-Assisted Visualization Workshop, Sacramento, CA, Oct 2007.
[PDF] (751KB) | [WMV] (10.8MB) | [PPT] (4.7MB)

Kwan-Liu Ma, Chaoli Wang, Hongfeng Yu, and Anna Tikhonova. In-Situ Processing and Visualization for Ultrascale Simulations. Journal of Physics: Conference Series (Proceedings of DOE SciDAC Conference), 78 (2007) 012043, Boston, MA, Jun 2007.
[PDF] (2.0MB)

Chaoli Wang, Antonio Garcia, and Han-Wei Shen. Interactive Level-of-Detail Selection Using Image-Based Quality Metric for Large Volume Visualization. IEEE Transactions on Visualization and Computer Graphics, 13(1):122-134, Jan/Feb 2007.
[PDF] (5.8MB) | [AVI] (28.1MB)

2006

Chaoli Wang. A Multiresolutional Approach for Large Data Visualization. PhD Dissertation, Department of Computer Science and Engineering, The Ohio State University. Dec 2006.
[PDF] (17.6MB)

Chaoli Wang and Han-Wei Shen. LOD Map – A Visual Interface for Navigating Multiresolution Volume Visualization. IEEE Transactions on Visualization and Computer Graphics (IEEE Vis 2006), 12(5):1029-1036, Sep/Oct 2006.
[Presented at IEEE Visualization 2006]
[PDF] (2.1MB) | [AVI] (25.4MB) | [PPT] (5.5MB)

Sean Ahern, Jamison R. Daniel, Jinzhu Gao, George Ostrouchov, Ross J. Toedte, and Chaoli Wang. Multi-Scale Data Visualization for Computational Astrophysics and Climate Dynamics at Oak Ridge National Laboratory. Journal of Physics: Conference Series (Proceedings of DOE SciDAC Conference), 46 (2006) 550-555, Denver, CO, Jun 2006.
[PDF] (528KB)

2005

Chaoli Wang and Han-Wei Shen. Hierarchical Navigation Interface: Leveraging Multiple Coordinated Views for Level-of-Detail Multiresolution Volume Rendering of Large Scientific Data Sets. In Proceedings of International Conference on Information Visualisation, London, England, pages 259-267, Jul 2005.
[PDF] (1.1MB) | [AVI] (17.0MB zipped)

Chaoli Wang, Jinzhu Gao, Liya Li, and Han-Wei Shen. A Multiresolution Volume Rendering Framework for Large-Scale Time-Varying Data Visualization. In Proceedings of Eurographics/IEEE VGTC Workshop on Volume Graphics, Stony Brook, NY, pages 11-19, Jun 2005.
[PDF] (1.3MB) | [PPT] (4.1MB)

Jinzhu Gao, Chaoli Wang, Liya Li, and Han-Wei Shen. A Parallel Multiresolution Volume Rendering Algorithm for Large Data Visualization. Parallel Computing (Special Issue on Parallel Graphics and Visualization), 31(2):185-204, Feb 2005.
[PDF] (535KB)

2004

Chaoli Wang, Jinzhu Gao, and Han-Wei Shen. Parallel Multiresolution Volume Rendering of Large Data Sets with Error-Guided Load Balancing. In Proceedings of Eurographics Symposium on Parallel Graphics and Visualization, Grenoble, France, pages 23-30, Jun 2004.
[Invited to Submit an Extended Version to Parallel Computing]
[PDF] (538KB)

Chaoli Wang and Han-Wei Shen. A Framework for Rendering Large Time-Varying Data Using Wavelet-Based Time-Space Partitioning (WTSP) Tree. Technical Report OSU-CISRC-1/04-TR05, Department of Computer and Information Science, The Ohio State University, 8 pages, Jan 2004.
[PDF] (1.2MB)

2003

Jonathan Woodring, Chaoli Wang, and Han-Wei Shen. High Dimensional Direct Rendering of Time-Varying Volumetric Data. In Proceedings of IEEE Visualization Conference, Seattle, WA, pages 417-424, Oct 2003.
[PDF] (894KB) | [MPG] (31.3MB)

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