Maxi San Miguel
- IFISC (CSIC-UIB)
- Campus Universitat de les Illes Balears E-07122 Palma de Mallorca. Spain
- Oficina 213
- +34 971 17 32 29
- Contact
Perfil
Founding Director of IFISC (2007-2021)
Fields of current interest: Statistical Physics, Stochastic processes, Nonequilibirum phenomena, Nonlinear phenomena, Spatiotemporal complexity, Complex Networks, Computational Social Sciences. Contributions also in Nonlinear and Quantum Optics, Photonics and Semiconductor lasers. Open to any creative scientific challenge.
Topics and Collaborators
Google scholar profile: maxi san miguel
ResearcherID: G-3224-2015
ORCID: 0000-0001-6237-425X
Publicacions recents
Detecting zealots in the Noisy Voter Model using Bayesian inference
Alvarez-Sanchez, Miguel (Supervisors: Tobias Galla and Maxi San Miguel)Master Thesis (2021)
Information processing in homophilic and heterophilic social networks: simple vs. complex contagion
Díaz Díaz, Fernando (Supervisors: Maxi San Miguel, Sandro Meloni)Master Thesis (2021)
Computational Social Models (CSIC Libro Blanco)
Galla, Tobias; San Miguel, Maxi; Toral, RaulCSIC Libro Blanco, , (2021)
Introduction to the Chaos Focus Issue on the Dynamics of Social Systems
San Miguel, Maxi; Toral, RaulChaos 30, 12041 (2020)
Absorbing transition in a coevolution model with node and link states in an adaptive network: Network fragmentation transition at criticality
Saeedian, Meghdad; San Miguel, Maxi; Toral, RaulNew Journal of Physics 22, 113001 (2020)
Projectes de recerca recents i vigents
PACSS
Physics approach to complexity in sociotechnical systems
I.P.: Sandro Meloni, Jose Javier Ramasco, Maxi San Miguel, Raúl Toral
This project, Physics approach to complexity in sociotechnical systems (PACSS), wants to contribute to the understanding of sociotechnical phenomena from the perspective provided by the application of the modern field of complex ...
SMOF
Strategic Manipulation in Dynamic Processes of Opinion Formation on Multiplex Networks
I.P.: Maxi San Miguel
The project generally aims at a better understanding of influence maximization in dynamical models of opinion formation on large-scale multiplex networks. The research combines numerical simulation and approximation techniques to understand opinion ...