Graphics4Science: Computer Graphics for Scientific Impacts

Course Description

Computer graphics, often associated with films, games, and visual effects, has long been a powerful tool for addressing scientific challenges—from its origins in 3D visualization for medical imaging to its role in modern computational modeling and simulation. This course explores the deep and evolving relationship between computer graphics and science, highlighting past achievements, ongoing contributions, and open questions that remain. We show how core methods, such as geometric reasoning and physical modeling, provide inductive biases that help address challenges in both fields, especially in data-scarce settings. To that end, we aim to reframe graphics as a modeling language for science by bridging vocabulary gaps between the two communities. Designed for both newcomers and experts, Graphics4Science invites the graphics community to engage with science, tackle high-impact problems where graphics expertise can make a difference, and contribute to the future of scientific discovery.

Schedule

Materials

Interested?

Join Graphics4Science community on Discord, WeChat, and Slack

Speakers

Peter Yichen Chen
University of British Columbia

Minghao Guo
CSAIL, MIT

Hanspeter Pfister
Harvard University

Ming Lin
University of Maryland College Park

William Freeman
CSAIL, MIT

Qixing Huang
The University of Texas at Austin

Han-Wei Shen
The Ohio State University

Wojciech Matusik
CSAIL, MIT

Acknowledgement

We thank Siyuan Chen, Liwen Wangcao for their help in preparing the course website and group chats.

BibTex

@article{yichen2025graphics4science,
    title={Graphics4Science: Computer Graphics for Scientific Impacts},
    author={Yichen Chen, Peter and Guo, Minghao and Pfister, Hanspeter and Lin, Ming and Freeman, William and Huang, Qixing and Shen, Han-Wei and Matusik, Wojciech},
    journal={SIGGRAPH 2025 Course},
    year={2025}
}