Mesh Generation

Principal investigators: Betul Atalay (TOBB University of Economics and Technology), Suneeta Ramaswami (Rutgers and Camden), Dianna Xu.

Polygon meshes define the shape of digital objects and are needed in digital modeling and simulations of all types. This research focuses on generating meshes that have good quality guarantee, in terms of minimum/maximum angles and aspect ratio. We have a number of active sub projects and directions and can accommodate interests towards both theoretical and implementation work.

Geometric Algorithms and Computational Geometry

Principal investigators: Dianna Xu.

This research focuses on applied problems in Computer Graphics, Vision and Imaging, with methods strongly rooted in geometric analysis and algorithms. The topics covered sit at the intersection of pure mathematics and application-driven Computer Science.

Creative Computation

Principal investigators: Ira Greenberg (Southern Methodist University), Dianna Xu, Deepak Kumar.

This project explores the use of algorithms and computation as a medium for visual expression. Learning materials to introduce creative computation as a context for introductory computation are being developed.

Data Analysis and Visualization

Principal investigators: Dianna Xu.

This research explores geometric and topological methods in data analysis and visualization.

Science of Information

Principal investigators: Deepak Kumar (Bryn Mawr College). Other collaborators include Howard University, MIT, Princeton University, Purdue University, Stanford University, Texas A&M, University of California (Berkeley and San Diego), University of Hawaii, and University of Illinois..

The mission of the Center for Science of Information is to advance science and technology through a new quantitative understanding of the representation, the communication, and processing of information in biological, physical, social, and engineered systems. The Center for Science of Information is a National Science Foundation Science and Technology Center made possible by grant NSF CCF-0939370.