Courses
|
Course Offerings |
ECE 510
|
Title:
"Computational Modeling and Optimization"
Instructor: Jorge More and Todd Munson
Schedule: Autumn
2002
Objective: This course is an advanced introduction to the modeling of scientific
computing problems with optimization techniques. Two major areas
will be covered: optimal control/design and equilibrium problems.
Students will learn how to formulate, solve, and analyze these
optimization problems. In addition, the course will cover the required
background on the required modeling and algorithmic aspects. |
Two
new courses were developed in 2001-2002: |
ES_APPM
346 |
Title:
"Modeling
and Computation in Science and Engineering"
Instructor: David
Chopp
Schedule: Winter
2002, to be taught every two years.
Objective: Teach
numerical methods for ordinary differential equations for models that
arise in various engineering disciplines. The novelty in the course
is the switch from straight numerical analysis to a more application/project
oriented approach. Applications will vary from year to year. This
year covered simple incompressible fluid flow, chemical reactions,
drug level maintenance, and neuron synapse firing among others. |
CS
395
Special Topics
|
Title:
"Algorithmic Research for E-Commerce"
Instructor:
Ming Kao
Schedule: Spring 2002, to be taught every two years.
Objective: This course focuses on various aspects of E-commerce
that have non-trivial algorithmic components. Example topics include
mechanism design (such as auction), data mining, network security,
and massive data sets. The goal is to enable students to start doing
research in this area as soon as possible.
|
This
course was taught in Spring, 2000: |
CS
395 Special Topics |
Title:
"Computing on Computational Grids"
Instructor:
Jennifer Schopf
Schedule:
Objective: Parallel distributed computing, also known as metacomputing
or heterogenous computing, involves distributed resources cooperating
to solve a single parallel application. This course is intended to
be a general overview of current work in distributed parallel computing.
To this end, we will be discussing current work in applications, infrastructure,
operating systems, resource management approaches, scheduling, performance
analysis, and other subjects according to interest. |
|