CSE 8803-MGA: Massive Graph Analysis

Georgia Tech, Fall 2012

Tuesday/Thursday 12:05pm - 1:25pm, CoC Bldg. 102
Instructor: Dr. David A. Bader

Office: KACB 1320
Office Hours: Tuesday 9:25am - 10:25am

Teaching Assistant: Abhishak Abhishak, aabhishek3@gatech.edu
TA Office Hours: Wednesday 4:00pm - 5:00pm, Klaus Room 3337

Class Mailing List:

Course Description:

Emerging real-world graph problems include detecting community structure in large social networks, improving the resilience of the electric power grid, and detecting and preventing disease in human populations. Unlike traditional applications in computational science and engineering, solving these problems at scale often raises new challenges because of sparsity and the lack of locality in the data, the need for additional research on scalable algorithms and development of frameworks for solving these problems on high performance computers, and the need for improved models that also capture the noise and bias inherent in the torrential data streams. In this course, students will be exposed to the opportunities and challenges in massive data-intensive computing for applications in computational biology, genomics, and security. This course will introduce students to designing high-performance and scalable algorithms for massive graph analysis. The course focuses on algorithm design, complexity analysis, experimentation, and optimization, for important ``big data'' graph problems. Students will develop knowledge and skills concerning:

Course Information:

Additional Readings: