Scott Rixner is an Associate Professor in the Computer Science & Electrical and Computer Engineering departments at Rice University. He leads the Rice Computer Architecture Group, and his research interests include media, network, and communications processing; the interaction between operating systems and computer architectures; and memory system architecture. During his doctoral studies, Rixner was the principal architect of the Imagine Stream Processor. His current research focuses on network server architecture, network virtualization, and memory system architecture.


More info: http://www.cs.rice.edu/~rixner/




E.g., Saturday, April 25, 2015
E.g., Saturday, April 25, 2015
E.g., Saturday, April 25, 2015
Mar 27th 2015

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Students will refine their programming skills as well as learn the basics of creating efficient solutions to common computational problems.

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Mar 27th 2015

This two-part course is designed to be a fun introduction to the basics of programming in Python. Our main focus will be on building simple interactive games such as Pong, Blackjack and Asteroids.

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Feb 13th 2015

This two-part course is designed to be a fun introduction to the basics of programming in Python. Our main focus will be on building simple interactive games such as Pong, Blackjack and Asteroids.

8.4
Average: 8.4 (5 votes)
Feb 13th 2015

This two-part course introduces the basic mathematical and programming principles that underlie much of Computer Science. Students will refine their programming skills as well as learn the basics of creating efficient solutions to common computational problems.

0
No votes yet
Aug 25th 2014

Experienced Computer Scientists analyze and solve computational problems at a level of abstraction that is beyond that of any particular programming language. This class is designed to train students in the mathematical concepts and process of "Algorithmic Thinking", allowing them to build simpler, more efficient solutions to computational problems.

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