Friday, March 8, 2013 - 10:00am to 11:15am
KEC 1007

Speaker Information

Erin Chambers
Assistant Professor
Department of Mathematics and Computer Science
Saint Louis University


The question of how to measure similarity between curves in various settings has received much attention recently, motivated by applications in GIS data analysis, medical imaging, and computer graphics. While geometric measures such as the Hausdorff and Frechet distance have efficient algorithms, measures that take the underlying topology of the space are relatively new and unexplored. Several candidates have been proposed in recent years, but many of these are only tractable in restricted settings, and surprisingly little is known about their practicality. We will survey known results (both geometric and topological) in the first part of the talk, and then focus on new algorithmic results for the topological measures in the second half. The talk will conclude with open questions and possible new directions in this area.

Speaker Bio

Erin Chambers is an Assistant Professor at Saint Louis University in the Department of Mathematics and Computer Science. She received her PhD in Computer Science in 2008 and her Masters in Mathematics in 2005, both from the University of Illinois at Urbana-Champaign; in 2011, she was a Visiting Research Professor at Saarland University. She was the recipient of an NSF CAREER award as well as an NSF graduate research fellowship. Her primary research interests focus on computational topology and geometry, as well as combinatorics and combinatorial algorithms.