Guido Caldarelli

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BIO:

Guido Caldarelli is Director of the Institute of Complex Systems (ISC-CNR) in Rome and Professor of Theoretical Physics at Ca’ Foscari University of Venice. He is a Fellow of the London Institute for Mathematical Sciences (LIMS) and Founder of the RARA Foundation and Factory—initiatives dedicated to the discovery of new materials. A specialist in statistical physics, his research focuses on complex networks. Prof. Caldarelli earned his physics degree at Sapienza University of Rome, followed by a PhD at SISSA, Trieste. He has held postdoctoral positions at the University of Manchester and the University of Cambridge before returning to Italy to continue his academic career.

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Jessica Davis

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BIO:

Jessica Davis is a Research Assistant Professor in the Department of Public Health and Health Sciences at Bouvé College and a member of MOBS Lab. Her research combines network science methods with data-driven epidemic modeling to respond to emerging infectious disease outbreaks. Her work aims to inform public health policies and enhance preparedness for future outbreaks by bridging the gap between theory and practice. She received her PhD in Network Science from Northeastern University, where she investigated the impact of cryptic transmission and travel restrictions during the early stages of the COVID-19 pandemic.

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Federico Levi

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BIO:

Federico Levi is Deputy Editor, Physics and Computing at Nature. His studies began at the University of Milan, where he specialized in the dynamics of open quantum systems. He then obtained his PhD from the University of Freiburg where he studied entanglement theory and energy transfer in disordered systems, with a focus on identifying quantum effects in biological processes.

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Miriam Redi

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BIO:

Miriam Redi is Research Manager at the Wikimedia Foundation and Visiting Research Fellow at King’s College London. Previously, she worked as a Research Scientist at Yahoo! Labs (Barcelona) and Nokia Bell Labs (Cambridge). She holds a PhD from EURECOM (Sophia Antipolis) and conducts research in social multimedia computing, with a focus on fair, interpretable, multimodal machine-learning systems for advancing knowledge equity.

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