Junpeng Wang

Staff Research Scientist

Research Areas: Visual Analytics, Explainable AI, and Deep Learning 

Junpeng Wang, Visa Research scientist.

Biography

Dr. Junpeng Wang joined Visa Research as a Staff Research Scientist in June 2019. He received his Ph.D. in Computer Science from The Ohio State University in 2019, M.S. in Computer Science and Application from Virginia Polytechnic Institute and State University in 2015, and B.Eng. in Software Engineering from Nankai University in 2011.

As a member of the Data Analytics team, Junpeng’s research interests are broadly in explainable artificial intelligence (Explainable AI), visual analytics, and deep learning. Specifically, he designs and develops novel visual designs and friendly user interactions to facilitate the interpretation and diagnosis of deep learning models. He has published multiple papers in international conferences and journals, including IEEE VIS, IEEE PacificVis, IEEE TVCG, Information Visualization, and others. He is the recipient of multiple best paper awards, including the Best Paper Award at IEEE PacificVis 2018, the Best Paper Honorable Mention Award at IEEE VIS (VAST) 2018, and the Best Paper Award at IEEE VIS (SciVis) 2019.

Conferences

  1. He, W., Wang, J., Guo, H., Wang, K. C., Shen, H. W., Raj, M., ... & Peterka, T. (2020). InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations. IEEE Transactions on Visualization and Computer Graphics, 26(1), 23-33.
  2. Wang, J., Gou, L., Zhang, W., Yang, H., & Shen, H. W. (2019). DeepVID: Deep Visual Interpretation and Diagnosis for Image Classifiers via Knowledge Distillation. IEEE Transactions on Visualization and Computer Graphics, 25(6), 2168-2180.
  3. Wang, J., Gou, L., Shen, H. W., & Yang, H. (2019). DQNViz: A Visual Analytics Approach to Understand Deep Q-Networks. IEEE Transactions on Visualization and Computer Graphics, 25(1), 288-298.
  4. Wang, J., Hazarika, S., Li, C., & Shen, H. W. (2019). Visualization and Visual Analysis of Ensemble Data: A Survey. IEEE Transactions on Visualization and Computer Graphics, 25(9):2853-2872
  5. Wang, J., Liu, X., & Shen, H. W. (2019). High-Dimensional Data Analysis with Subspace Comparison Using Matrix Visualization. Information Visualization, 18(1), 94-109.
  6. Wang, J., Gou, L., Yang, H., & Shen, H.W. (2018). GANViz: A Visual Analytics Approach to Understand the Adversarial Game. IEEE Transactions on Visualization and Computer Graphics, 24(6), 1905-1917.
  7. Wang, J., Liu, X., Shen, H.W., & Lin, G. (2017). Multi-Resolution Climate Ensemble Parameter Analysis with Nested Parallel Coordinates Plots. IEEE Transactions on Visualization and Computer Graphics, 23(1), 81-90.
  8. Wang, J., Yang, F., & Cao, Y. (2017). A Cache-Friendly Sampling Strategy for Texture-Based Volume Rendering on GPU. Visual Informatics, 1(2), 92-105.
  9. Wang, J., Elshehaly, M., & Cao, Y. (2015). Cylindrical Acceleration Structures for Large Hexahedral Volume Visualization. IEEE Symposium on Large Data Analysis and Visualization (IEEE LDAV), 25-31.
  10. Wang, J., Yang, F., & Cao, Y. (2015). Computation-to-Core Mapping Strategies for Iso-Surface Volume Rendering on GPUs. IEEE Pacific Visualization Symposium (IEEE PacificVis), 153-157.
  11. Wang, J., Yang, F., & Cao, Y. (2014). Cache-Aware Sampling Strategies for Texture-Based Ray Casting on GPU. IEEE Symposium on Large Data Analysis and Visualization (IEEE LDAV), 19-26.
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