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Reconstruction of complex networks from data

Grant number: 18/10349-4
Support Opportunities:Scholarships in Brazil - Doctorate
Start date: October 01, 2018
End date: June 30, 2022
Field of knowledge:Physical Sciences and Mathematics - Mathematics - Applied Mathematics
Principal Investigator:Tiago Pereira da Silva
Grantee:Edmilson Roque dos Santos
Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil
Associated research grant:13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry, AP.CEPID

Abstract

This project addresses the problem of predicting the occurrence of sudden changes of behaviour in complex systems from data. Such abrupt changes in behaviour are known as critical transitions and are observed in Ecology, Neuroscience, Medicine, and Technology. A recent breakthrough elucidates how the network interaction affects the emergent properties and opens the possibility to predict critical transitions by reconstructing the network dynamics from data. Therefore, in this project we aim at the reconstruction of network dynamics from data. Thus, from a single multivariate time-series we can reverse engineer the problem and obtain a model from data. Thereby, we can predict critical transitions from data which would be impossible otherwise. (AU)

News published in Agência FAPESP Newsletter about the scholarship:
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VEICULO: TITULO (DATA)
VEICULO: TITULO (DATA)

Scientific publications
(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)
ELDERING, JAAP; LAMB, JEROEN S. W.; PEREIRA, TIAGO; DOS SANTOS, EDMILSON ROQUE. Chimera states through invariant manifold theory. Nonlinearity, v. 34, n. 8, p. 5344-5374, . (18/10349-4, 15/25947-6, 13/07375-0)
Academic Publications
(References retrieved automatically from State of São Paulo Research Institutions)
SANTOS, Edmilson Roque dos. Reconstruction of sparse network dynamics from data. 2024. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.