Basic things to be apprised of:

  • Identifying marks:

    Deliverator: Prof. Peter Dodds.

    Lecture room and time: 102 Perkins, Tuesday and Thursday, 1:15 pm to 2:30 pm.

    Office hours:
    Tuesday and Thursday, after class, 2:30 to 3:15 pm; Wednesday, 11 to 11:55 am, Farrell Hall, Trinity Campus.

  • Content delivery:

    All episodes (recorded lectures) and slides are organized here and here, and a youtube playlist is here.

    Follow @networksvox for course updates and fun things.

    Team members can interact on Slack [private].

  • Prerequisites:

    The level will be graduate/advanced undergraduate and students are expected to have strong general backgrounds in mathematics, statistics, and coding.

    Principles of Complex Systems is the main prerequisite, though students may request an override.

  • Series:

    Principles of Complex Systems and Complex Networks form a highly interconnected two course sequence.

    Both courses are part of the curriculum for the Graduate Certificate in Complex Systems and the Masters of Science in Complex Systems and Data Science at the University of Vermont.

Synopsis for CocoNuTs:

Complex networks crucially underlie an enormous array of large-scale systems, from physical to abstract. Networks distribute and redistribute information, water, food, and energy. Networks can be constituted by information carrying cables, predator-prey links in ecologies, economic interdependencies, relationships carried in people's minds, and the connections between domains of knowledge.

With breakthroughs in disciplines running from physics to sociology, many advances have been made in understanding the structure and dynamics of all manner of complex networks such as the Internet, power grids, social and organizational networks, social and biological contagion, biochemical networks, and transportation networks. Fundamental features are robustness and fragility, adaptability, and performance.

In CocoNuTs, we will explore the now vast and always evolving field of complex networks by working closely with foundational research articles, developing mathematical and algorithmic results where they exist, analyzing real networks, and carrying out simulations.

A recent episode: