Prof. Cristina Masoller
research on complex systems and data analysis
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Complex systems
are non-linear systems made up of a large number of interacting units. Our research focuses
on characterizing and predicting the behavior of complex systems using
appropriate data analysis tools. We are interested in identifying early
warning indicators of upcoming extreme events or critical transitions. |
Watch the videos to see how the how seasons evolve
during a normal
year, a El
Niño year and a La Niña year
(temporal evolution of the cosine of the Hilbert phase, D.
Zappala et al., Chaos 2020). |
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Recent
publications Identifying and anticipating the
threshold bifurcation of a complex laser with permutation entropy J. Gancio, C. Masoller, M. Marconi Phys. Rev. Lett.
135, 093802 (2025) J. Gancio, G. Tirabassi, C. Masoller, M. Barreiro, submitted (2025) J. Gancio, C. Masoller, G. Tirabassi Chaos 34, 043130 (2024) Inferring
the connectivity of coupled oscillators from event timing analysis R. P. Aristides, H. A. Cerdeira,
C. Masoller, G. Tirabassi Chaos, Solitons & Fractals 182, 114837 (2024) Recent
presentations Tercera Reunión Conjunta AFA-SUF 2025, La Plata, Argentina, September 2025 Invited talk: Metodologías
de análisis de datos no lineales para la investigación de sistemas complejos XXV Congreso de Física Estadística (FisEs’25) Santiago de Compostela, Spain, June, 2025 Invited talk: Nonlinear
data analysis tools for complex systems research Classical ordinal patterns and beyond (COPAB 2025),
Twente, The Netherlands, April 2025 Invited talk: Characterizing
and detecting regime transitions by using ordinal analysis Book Networks
in Climate (H. A.
Dijkstra, E. Hernandez-Garcia, C. Masoller and M. Barreiro,
Cambridge University Press 2019, ISBN: 9781316275757) |
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Funding Agencia Estatal de
Investigación PID2024-160573NB-I00 (2025-2028) Doctoral Network BE-LIGHT: Improving BiomEdical diagnosis through LIGHT-based
technologies and machine learning (2023-2027) |
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