Course Description

CS-232: Geometric Algorithms

CS-232 is a newly developed course. It is introduced to provide interdiciplinary education to undergraduate students in computer science as well as to undergraduate students in applied computational science and engineering. This course is designed to help improve students' algorithmic and analytical maturity, to show studends interesting algorithmic applications in scientific computing and scientific visualization, and to bridge interdiciplinary educational gap among computer science, applied mathematics, and computational science and engineering.

Why Computational Geomtry?

In various interdiciplinary applications such as scientific computing, computer vision, scientific visualization, computational biology, computer graphics, robotics, network design, and information organization, we need algorithms to solve various geometric problems and design efficient geometric data structures. This course will make our students better prepared for getting into our 300-level courses as well as other interdiciplinary courses.

One of the goals of this course is to provide an environment to learn linear algebra in the context of geometric applications and algorithms and to learn geometric concepts and structures using the language of linear algebra.

Because this may be the first course for many of you to study the modern theory of algorithms, and we will be covering a great deal, I expect the course to be challenging, both in terms of the workload and the difficulty of the material. You should be prepared to do a lot of work outside of class. The payoff will be that you will learn a lot of both useful and interesting things.


CAS CS 112 or CS 113;

We will try to make this course as self-contained as possible.


TR 2:00-3:30 PM in room COM 213


CAS CS330 A2 648134 Monday 3:00pm-4:00pm in CAS 204A
CAS CS330 A3 648147 Tuesday 12:00-1:00pm in CAS B20


Quiz 1: Tuesday, Feb. 3 (in class)

Midterm: Thursday, Feb. 26 (in class)

Quiz 2: Tuesday, March 30 (in class)

Final: TBA

Performance self-monitoring:

The grade statistics for hw's and tests will be published on the web.

The danger zone is one standard deviation below average or worse.

If you find yourself in this danger zone more than a couple times - you have a good chance to fail the class. If you are in the danger zone a few times, then (1) talk to the instructor (and/or TF) without delay; (2) make sure that your performance improves.


Professor Shang-Hua Teng

Office: MCS-276
Office Hours: Tuesday 12:30-2:00pm, Thursday 12:30-2:00pm (or by appointment)
Office Phone: 358-2596

Teaching Fellow

Scott Russell

Office: PSY 223
Office Hours: Wednesday 2--5 pm (or by appointment)
Office Phone: 617 253 8921


Handouts on Geometric Algorithms

Introduction to Linear Algrbra, by Gilbert Strang 3rd edition, 2003.

Useful links