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Topology studies how a shape or object is
connected. In the past couple decades, there has
been an increased interest in the development and
use of topological methods for solving various
problems in science and engineering. This new line
of study is called Computational Topology,
Topological Data Analysis (TDA),
or Applied
Algebraic Topology. Computational topology
combines topological results with efficient
efficient algorithms to analyze data and solve
problems in many fields—biomedicine,
phenomics, machine learning, computer graphics and
image analysis, sensor networks, robotics,
geography, and several others. For motivation, see
my TEDx
talk on how TDA helps to find hidden
structures in data.
This course will present an introductory,
self-contained overview of computational
topology. There are no prerequisites, but
mathematical sophistication at the senior
undergraduate level and some familiarity with the
use of computer packages such as Matlab or Python
are expected. We will cover basic concepts from a
number of areas of mathematics, such as abstract
algebra, algebraic topology, and optimization. We
will also look at algorithms and data structures,
and efficient software for analyzing the topology of
point sets and shapes.
While there is
a recommended
book, we will rely a lot on handouts and
class notes. Material from a few recent (and
not-so recent) papers will also be
covered. Evaluation will be done through
homework (around 6 assignments) and a course
project. No exams will be given.
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