• I.P.: Massimiliano Zanin
  • Coordinador: Massimiliano Zanin
  • Data d'inici: 1 de març de 2020
  • Data de finalització: 28 de febrer de 2025

This project is an ERC Starting Grant of panel SH2, "Institutions, Values, Environment and Space". Air transport has by and large been studied as a transportation process, in which different elements, e.g. aircraft or passengers, move within the system. While intuitive, this approach entails several drawbacks, including the need for large-scale simulations, the reliance on real data, and the difficulty of extracting macro-scale conclusions from large quantities of micro- scale results. The lack of a better approach is in part responsible for our inability to fully understand delay propagation, one of the most important phenomena in air transport.

ARCTIC proposes an ambitious program to change the conceptual framework used to analyse air transport, inspired by the way the brain is studied in neuroscience. It is based on understanding air transport as an information processing system, in which the movement of aircraft is merely a vehicle for information transfer. Airports then become computational units, receiving information from their neighbours through inbound flights under the form of delays; processing it in a potentially non-linear way; and redistributing the result to the system as outbound delays. As already common in neuroscience, such computation can be made explicit by using a combination of information sciences and statistical physics techniques: from the detection of information movements through causality metrics, up to the representation of the resulting transfer structures through complex networks and their topological properties. The approach also entails important challenges, e.g. the definition of appropriate metrics or the translation of the obtained insights into implementable policies.
ARCTIC’s methodology will be used over the next five years to characterize and model delay propagation, as well as to limit its societal and economic impact.


  • Massimiliano Zanin

    Massimiliano Zanin

Publicacions recents

The AIMe registry for artificial intelligence in biomedical research

Julian Matschinske, ..., Massimiliano Zanin, Olga Zolotareva, Jan Baumbach & David B. Blumenthal
Nature Methods , (2021)

Ordinal patterns-based methodologies for distinguishing chaos from noise in discrete time series

Zanin, Massimiliano; Olivares, Felipe
Communications Physics 4, 190 (2021)

Leveraging network analysis to evaluate biomedical named entity recognition tools

Eduardo P. García del Valle; Gerardo Lagunes García; Lucía Prieto Santamaría; Massimiliano Zanin; Ernestina Menasalvas Ruiz; Alejandro Rodríguez-González
Scientific Reports 11, 13537 (2021)

Trends in Incidence and Transmission Patterns of COVID-19 in Valencia, Spain

Carolina Romero García; Adina Iftimi; Álvaro Briz-Redón; Massimiliano Zanin; Maria Otero; Mayte Ballester; José de Andrés; Giovanni Landoni; Dolores de las Marinas; Juan Carlos Catalá Bauset; Jesus Mandingorra
JAMA Network Open 4, e2113818 (2021)

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