Invited Speakers
 Alexander Bobenko, Technische Unversitaet Berlin:
Glueing a convex polytope: a constructive proof of Alexandrov's theorem
We present a constructive proof of Alexandrov's theorem on existence of
a convex polytope with a given metric on the boundary. The idea is to do
a deformation in the class of so called generalized convex polytopes
with positive curvature. The proof gives rise to a numerical algorithm
that was implemented in a computer program which will be demonstrated.
(Joint work with Ivan Izmestiev)
 Timothy Chan, University of Waterloo: Computational Geometry on the Word RAM
In this talk, I will describe recent advances in geometric algorithms
on the "transdichotomous" word RAM model. Algorithms that can sort n
integers in time better than the comparisonbased n log n lower bound
have been known for quite some time. I will show that many of the
favorite problems in our fieldfor example, 3d convex hulls,
2d Voronoi diagrams, linesegment intersection, and offline point
locationcan also be solved in o(n log n) time for integer input.
At least one interesting recurrence will be encountered, open problems
will be mentioned, and issues concerning the word RAM vs. the more
"traditional" real RAM will be discussed. (Joint work with Mihai Patrascu)
 Martin Demaine, MIT:
Mathematics is Art
This talk will describe my explorations in art and mathematics and
their interrelation. Both art and mathematics are founded on the
power of creativity and ideas, followed by precise execution within
the medium. Topics include glass blowing, performance art, puzzles,
origami, architecture, and hinged dissections. In addition to being
entertaining, this talk will announce and describe a new solution
to an open problem.
 Robert Ghrist, University of Illinois:
Euler characteristic for data aggregation
This work is motivated by a fundamental problem in
sensor networks  the need to aggregate redundant
sensor data across a network. We focus on a simple
problem of counting targets with a network of sensors
that can count nearby targets, but cannot identify
or localize them.
We show a clear, clean relationship between this
problem and the topology of constructible sheaves.
In particular, an integration theory from sheaf theory
that uses Euler characteristic as a measure provides
a computable, robust, and powerful tool for data
aggregation. (Joint work with Y. Baryshnikov, Alcatel/Lucent)
