用计算机图形技术解决科学难题，打通科研与图形领域的沟通壁垒。
Graphics4Science: Computer Graphics for Scientific Impacts
- 以几何推理和物理建模为桥梁，连接图形学与科学问题
- 在数据稀缺场景下，利用图形方法提升科学建模效率
- 适合想跨界解决真实科学问题的图形学研究者
计算机图形学常与影视、游戏和视觉特效关联，但其根源在于医学影像的三维可视化，并持续在现代计算建模与仿真中发挥作用。本课程探讨计算机图形学与科学之间日益深化的关系，回顾历史成就、当前贡献及未解问题。我们指出几何推理与物理建模等核心技术为两领域提供归纳偏置，在数据稀缺情境中尤为关键。为此，课程旨在将图形学重新定位为科学的建模语言，弥合两个社区间的术语鸿沟。面向初学者与专家，Graphics4Science 邀请图形学界参与具有高影响力的科学挑战，发挥图形专长，推动科学发现的未来。更多详情见课程网站：https://graphics4science.github.io
原文摘要 · Abstract (English)
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. Additional details are available on the course website: https://graphics4science.github.io
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