Physics, Complex Systems & Data Analysis · Now: Capturing spatial correlations by ordinal analysis in real world systems.
I have a Bachelor's and a Master's degrees in physics from Universidad de la República (UdelaR - Uruguay), and a PhD in Computational and Applied Physics from Universitat Politècnica de Catalunya (UPC - Spain).
My main interests are Nonlinear Dynamics, Complex Systems and Complex Networks. During my Master's I have focused mainly in Spectral Graph Theory, studying the dependance of the eigenvalue spectra of complex networks with the network's size, in order to determine if they are extensive. I have also worked on other network-related topics, such as: synchronisation, community detection, resistance distance, and eigenvalue-eigenvector identity.
During my PhD I applied ordinal patterns/permutation entropy methods in spatially extended systems. I used these methods to uncover spatial correlations, and studied if they have a preferred direction (anisotropy), and what information can be extracted from it. I care that these methods can be also applied to real world systems, thus I have analysed medical (EEG) and climate data.
Currently, I continue to work in generalising and applying these methods, mainly to use them as Early Warning Signal of critical transitions, and to characterise spatially extended complex systems. In particular, I am focused in the characterisation of the spatial structure of Reaction-Diffusion systems from wave propagation data, which could be applied to the analysis of the heart's dynamics.
I have over 800 hours of teaching experience, including 120 hours of lectures. My duties as a teacher have included: problem set design, problem set sessions, and students' evaluation. I have taught introductory and intermediate level courses in Math and Physics, such as: Introductory Physics (classical mechanics), Electromagnetism, Modern Physics, Thermodynamics, and Differential Equations. I have also filled in as a lecturer for an introductory physics course (Physics 101) in two editions. Now I teach introductory courses in experimental physics.
Spatial analysis of real world systems (using medical and climate data) by ordinal patterns/permutation entropy methods. I focus in studying if the spatial correlations have any preferred direction (anisotropy). I also teach introductory courses in experimental physics.
Ordinal analysis of the turn-on dynamics of multimode lasers.
Analysis of the diffusion tensor of anisotropic excitable media.
Numerical simulations and theoretical derivations for the Chaos, Networks and Synchronisation lines of research of the Nonlinear Dynamics group. Students' evaluation, problem sets design and problem sessions in introductory and intermediate physics and math courses. Lecturer in introductory physics.
Read my thesis (in spanish): Sincronización y extensividad de mapas acoplados en redes regulares.
Legend: Talk, Poster, School, Workshop.
Ordinal analysis of EEG data in order to characterise the underlying dynamics, specifically to distinguish different states of the brain related to the eyes and motor imagery task.
We use ordinal analysis to uncover spatial correlations and track their evolution in time. With this modern approach, and its unprecedented use in climate science, we have identified small scale differences between different models of global reanalysis, and trends in the spatial structure of the sea surface temperature.
By means of spatial permutation entropy (SPE) methods, we intend to estimate the fast diffusion direction in anisotropic 2D Aliev-Panfilov systems. We pretend to apply this methodology to real cardiac data, in order to find the orientation of the cardiac muscle fibers.