Renaud is an associate professor at the Mathematical Institute of Oxford University, investigating processes taking place on large networks.
In the episode, we talk about his story in science, the joy and value of exploring without a particular purpose, doing a PhD without publishing any papers, … and how reading classical texts by Boltzmann and others early on has shaped the work Renaud does even to this day.
When we get to the paper, we talk about Renaud’s recent work “Variance and covariance of distributions on graphs” (1) with co-authors Karel Devriendt and Samuel Martin-Gutierrez.
Our Episode 4 guest, Leidy Klotz, is a Professor at the University of Virginia. He studies the science of design: how we transform things from how they are – to how we want them to be. Leidy wants to apply his work outside of academia. He wants address climate change and systemic inequality, Leidy also works directly with organizations including the World Bank.
This episode’s guest is Dirk Brockmann. Dirk is a physicist and complex systems researcher. He’s a professor at the Department of Biology, Humboldt University of Berlin and the Robert Koch Institute, Berlin. Berfore returning to his native Germany, he was a professor at Northwestern University.
Colloquium Virtual Complexity at C3-UNAM Universities for Science Consortium
“Computational Epidemiology at the time of COVID-19” Alessandro Vespignani Network Science Institute at Northeastern University
Abstract: The data science revolution is finally enabling the development of large-scale data-driven models that provide real- or near-real-time forecasts and risk analysis for infectious disease threats. These models also provide rationales and quantitative analysis to support policy-making decisions and intervention plans. At the same time, the non-incremental advance of the field presents a broad range of challenges: algorithmic (multiscale constitutive equations, scalability, parallelization), real-time integration of novel digital data streams (social networks, participatory platform, human mobility etc.). I will review and discuss recent results and challenges in the area, and focus on ongoing work aimed at responding to the COVID-19 pandemic.
Short Bio: Alessandro Vespignani is the Director of the Network Science Institute and Sternberg Family Distinguished University Professor at Northeastern University. He is a professor with interdisciplinary appointments in the College of Computer and Information Science, College of Science, and the Bouvé College of Health Sciences. Dr. Vespignani’s work focuses on statistical and numerical simulation methods to model spreading phenomena, including the realistic and data-driven computational modeling of biological, social, and technological systems. For several years his work has focused on the spreading of infectious diseases, working closely with the CDC and the WHO.
Complexity Digest 