Objectives and Outcomes
Information
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Instructors: Amarda Shehu amarda\AT\gmu.edu
Place and Time: Innovation Hall #136, M 4:30-7:10 pm
Office Hours: ENGR #4452, M 3:30-4:30 pm, F 11:30 am -1:30 pm
Outcomes
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The objective of this course is to introduce students to complex
systems and network-based treatments of such systems. The course will
emphasize the fundamental underpinnings of network science to
graph-theoretic concepts and graph algorithms and so will focus on
algorithmic, computational, and statistical methods of network
science. Students will also appreciate diverse applications in machine
learning, robotics, communications, biology, ecology, brain science,
sociology, and economics. The course will go beyond the strictly
structural concepts of small-world and scale-free networks, focusing
on dynamic network processes such as epidemics, synchronization, or
adaptive network formation.
