With the increasing growth and impact of machine learning and other math-intensive fields, it
is more important than ever to broaden access to mathematical notation. Can new visual …

Geospatial data is playing an increasingly critical role in the work of Earth and climate
scientists, social scientists, and data journalists exploring spatiotemporal change in our …

Contemporary proof assistants rely on complex automation and process libraries with
millions of lines of code. At these scales, understanding the emergent interactions between …

Vector graphics are an industry-standard way to represent and share visual designs.
Designers frequently source and incorporate styles from existing designs into their work …

Diagrams are essential tools for problem-solving and communication as they externalize
conceptual structures using spatial relationships. But when picking a diagramming …

Unstructured triangular and tetrahedral meshes are widely used in graphics, engineering,
and scientific computing due to their flexibility to represent objects with complex boundaries …

This paper develops a shape space framework for collision-aware geometric modeling,
where basic geometric operations automatically avoid inter-penetration. Shape spaces are a …

This paper describes an optimization-based framework for finding arrangements of 2D
shapes subject to pairwise constraints. Such arrangements naturally arise in tasks such as …

This article reports on a novel approach to integrate artificial intelligence into a digital
collaborative platform embedded with a problem-based mathematics curriculum. Using …

Mesh processing algorithms are often communicated via concise mathematical notation (eg,
summation over mesh neighborhoods). However, conversion of notation into working code …