About Me

I am a Ph.D. candidate in the Department of Computer Science and Engineering at the University of Notre Dame, working in the ND-VIS research group under the supervision of Prof. Chaoli Wang. Prior to this, I obtained my B.S. degree from Xidian University in 2022.

My exisiting research focuses on the intersection of scientific visualization, computer graphics, and machine learning, including volumetric data generation and compression, as well as 3D scene representation and editing. Recently, I’ve become especially interested in emerging techniques in 3D vision, such as foundation models and MLLMs, and I believe exploring their potential applications in scientific visualization is a fascinating direction.

Recent News

[2026.04] SGI is selected as a Highlight Presentation at CVPR 2026!
[2025.08] NLI4VolVis is selected as Best Paper Award for IEEE VIS 2025!
[2025.07] Three papers are accepted to IEEE VIS 2025!
[2024.12] iVR-GS is accepted by IEEE PacificVis TVCG-Track 2025!
[2024.07] StyleRF-VolVis is accepted by IEEE VIS 2024!
[2023.12] ECNR is accepted by IEEE PacificVis Conference Track 2024!

Publications

Star * indicates equal contribution,underline denotes supervised undergrad student

  1. SGI: Structured 2D Gaussians for Efficient and Compact Large Image Representation CVPR 26
    Zixuan Pan*, Kaiyuan Tang*, Jun Xia, Yifan Qin, Lin Gu, Chaoli Wang, Jianxu Chen, Yiyu Shi
    IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2026.
  2. SciVisAgentBench: A Benchmark for Evaluating Scientific Data Analysis and Visualization Agents arXiv
    Kuangshi Ai, Haichao Miao, Kaiyuan Tang, Nathaniel Gorski, Jianxin Sun, Guoxi Liu, Helgi I. Ingolfsson, David Lenz, Hanqi Guo, Hongfeng Yu, Teja Leburu, Michael Molash, Bei Wang, Tom Peterka, Chaoli Wang, Shusen Liu
    arXiv preprint, 2026.
  3. SVLAT: Scientific Visualization Literacy Assessment Test arXiv
    Patrick Phuoc Do, Kaiyuan Tang, Kuangshi Ai, Chaoli Wang
    arXiv preprint, 2026.
  4. TexGS-VolVis: Expressive Scene Editing for Volume Visualization via Textured Gaussian Splatting VIS 25
    Kaiyuan Tang, Kuangshi Ai, Jun Han, Chaoli Wang
    IEEE Transactions on Visualization and Computer Graphics (TVCG), 2026.
  5. MoE-INR: Implicit Neural Representation with Mixture-of-Experts for Time-Varying Volumetric Data Compression VIS 25
    Jun Han, Kaiyuan Tang, Chaoli Wang
    IEEE Transactions on Visualization and Computer Graphics (TVCG), 2026.
  6. NLI4VolVis: Natural Language Interaction for Volume Visualization via LLM Multi-Agents and Editable 3D Gaussian Splatting VIS 25
    Kuangshi Ai, Kaiyuan Tang, Chaoli Wang
    IEEE Transactions on Visualization and Computer Graphics (TVCG), 2026.
  7. iVR-GS: Inverse Volume Rendering for Explorable Visualization via Editable 3D Gaussian Splatting PVIS 25
    Kaiyuan Tang, Siyuan Yao, Chaoli Wang
    IEEE Transactions on Visualization and Computer Graphics (TVCG), 2025.
  8. Meta-INR: Efficient Encoding of Volumetric Data via Meta-Learning Implicit Neural Representation PVIS Short 25
    Maizhe Yang, Kaiyuan Tang, Chaoli Wang
    Proceedings of IEEE Pacific Visualization Conference (Visualization Notes), 2025.
  9. StyleRF-VolVis: Style Transfer of Neural Radiance Fields for Expressive Volume Visualization VIS 24
    Kaiyuan Tang, Chaoli Wang
    IEEE Transactions on Visualization and Computer Graphics (TVCG), 2025.
  10. ECNR: Efficient Compressive Neural Representation of Time-Varying Volumetric Datasets PVIS 24
    Kaiyuan Tang, Chaoli Wang
    Proceedings of IEEE Pacific Visualization Conference 2024.

Service

Reviewers

  • [VIS] IEEE Visualization Conference, Full Papers (2025)
  • [PVIS] IEEE Pacific Visualization Conference, Journal and Conference Track (2025)

MISC

One thing I find quite amusing is that although I’ve already published several papers during my PhD, due to visa issues and some unexpected circumstances, I’ve actually never attended any academic conference in person — I’m really grateful to my advisor for helping present some of my works. On one hand, I genuinely hope to have the chance to meet and connect with people face-to-face soon, but on the other hand, I can’t help but feel a strange kind of excitement about keeping this “record” going. 😂