Graphics-based methods are increasingly embedded directly in scientific and engineering workflows, where they influence interpretation, experimental design, and downstream decisions. As the stakes of these decisions continue to rise, there is a timely need to consolidate technical insights and advance graphics-driven approaches that emphasize physical grounding, numerical stability, and explicit treatment of uncertainty across domains.
Building on the strong engagement with the SIGGRAPH 2025 Graphics x Science course, the 2026 edition moves to a workshop format to enable deeper technical discussion and more active participation. The goal is to move beyond a catalog of applications and toward an actionable technical agenda for graphics-enabled science, with a unifying theme of translation: connecting computational methods to scientific constraints, evaluating progress when ground truth is limited, and packaging techniques into practical tools that domain experts can trust and iterate on.
We invite submissions on topics at the intersection of computer graphics and scientific discovery. We support two submission formats: 2-page extended abstracts and full papers (no page limit). All submissions must follow the ACM SIGGRAPH formatting guidelines.
We thank Siyuan Chen, Caoliwen Wang, and Kevin Chen for their help in preparing the course website, setting up group chats, and refining the slides.
