• Networks of courses and conferences

    A lot is happening on the network education front! Computer science students (and others) at the University of Vermont are currently 5 weeks into my new Algorithms for Complex Networks course. We are also currently planning and accepting contributed presentations for Contagion & Networks 2018, the second edition of our NetSci satellite event. Finally, I hope to announce a much larger network education project over the next few months! Stay tuned.

  • Summer update

    Two very interesting papers were published this month. The first is a Zika project with the Contagion on Networks team showing that the asymmetric transmission across sexes leads to a double epidemic transitions; the paper was published in PNAS. The second one is the result of an SFI working group, which started by studying the strategies of algae life cycles and ended up re-discovering game theory by studying political dynamics on modular networks; this crazy paper was published in Scientific Reports.

  • NetSci 2017 Satellite

    Antoine Allard, Ben Althouse, Sam Scarpino and I are organizing a satellite conference for NetSci 2017 called Contagion on Networks 2017 and focused on the dynamics of contagion. We are already receiving abstracts, and will fully consider all contributions sent to us before March 12.

  • New paper in PRE

    New paper out in PRE with Uttam Bhat and Munik Shrestha. We open an interesting new problem: Why is the emergence of k-core continuous in networks with triadic closure (transitive linking)? We find that triangles alone do not account for the richness of the phase transitions we observe, which hints at the critical role of overlapping triangles (non-trivial motifs). We are in dire need of better analytical tools to account for these overlapping motifs. To be continued…

  • New NSF grant on network comparison

    Joshua Grochow and I were awarded a grant from NSF’s Division of Mathematical Sciences. Our project is titled Network Comparison, a Cornerstone of the Foundations of Network Science. We should start the real work in the next few months, and we aim to come up with model-free tools of network comparison. To quote ourselves: “To break new ground, we must think in terms of structural distance rather than statistical inference.”

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