Shape Modeling

In order for our computers to deal with real world entities, we need an accurate digital representation of the geometric shapes involved. These representations typically break down the shape in question into an interconnected collection of simple objects called a mesh. Given the necessity of obtaining accurate and high-quality meshes in a multitude of disciplines from computer graphics to scientific simulations, the efficient generation of such meshes is a fundamental research problem relevant to many scientific communities.

My research in shape modeling leverages a deep understanding of surface models and sampling paradigms. During my PhD, I spent time at Google Research and Sandia National Labs working extensively on the theory and implementation of surface reconstruction algorithms with theoretical guarantees. Notably, my work at Sandia National Labs has been essential to the development of the first provably-correct algorithm for conforming Voronoi meshing: VoroCrust.

My experience working on mesh generation greatly influenced my research even in other areas. I have always been very passionate about geometry and continue to seek opportunities to learn more about surfaces and their discrete representations.