Dr Nicolas Rubido Obrer

Biography

Since January 2022 I am a Lecturer of the Institute for Complex Systems and Mathematical Biology (ICSMB), University of Aberdeen (UoA). Previously, I was an Adjunct Professor of the Physics Institute in the School of Sciences (IFFC), Universidad de la República (UdelaR), Uruguay. I was appointed at the IFFC after my Ph.D. (in Dec. 2014), working as part of the Non-Linear Physics group (NLP) and its experimental branch, the Laboratory of Instabilities in Fluids, which I remain as an associate researcher. From June 2020 up to January 2022 I worked as Research Fellow of the Aberdeen Biomedical Imaging Centre (ABIC) in a project involving the development of novel neuroimaging ways to classify Alzheimer's disease and mild-cognitive impairment from large-scale brain networks.

I have a Ph.D. in Physics from the UoA for the thesis: "The mathematical principles behind the transmission of Energy and Synchronisation in Complex Networks", which was supervised by Dr. Murilo S. Baptista and Prof. Celso Grebogi. The thesis got nominated to the Springer theses award "the best of the best" by the UoA, which after winning was published as a book (ISBN 978-3-319-22216-5). Its outcomes (including 5 publications) involve exact and approximate results for the behaviour and stability of complex systems, which are particularly useful when studying phase-angle stability at the transmission level of power-grid systems. Before my Ph.D., I got an M.Sc. in Physics from the UdelaR for the thesis: "Synchronisation of coupled electronic oscillators", which was supervised by Prof. Arturo C. Martí and Dr. Cecilia Cabeza. The thesis (including 3 publications) analyses the dynamics of electronic oscillators modelling gregarious fireflies, which I implemented using dual RC circuits and interactions via LED light pulses. My results include conclusions for the synchronisation of networks of generic piecewise oscillators, which are also helpful in understanding neural excitatory and inhibitory dynamics.

External Memberships

• Memberships

  • Scottish Imaging Network (SINAPSE), Researcher

  • Programa de Desarrollo de las Ciencias Básicas (PEDECIBA), Ministerio de Educación y Cultura (MEC), Uruguay - Associate Researcher

  • Sistema Nacional de Investigadores (SNI), Agencial Nacional de Investigación e Innovación (ANII), Uruguay - Associate Researcher

• Review Editor:
  • Frontiers in Computational Neuroscience
  • Frontiers in Network Physiology - Networks in the Brain System
  • Frontiers in Physics - Interdisciplinary Physics

Prizes and Awards

• Young Researchers Award – Dynamics Days Europe conference (supported by the European Physical Society, AIP publishing, and the Chaos journal), Greece 2016
• Springer theses award: “the best of the best” – Springer, Germany 2015
• SUPA Studentship prize (No. 1802), 2011 – Scottish Universities Physics Alliance

Research Overview

I am an Applied Mathematician with a Physics background in non-linear dynamics and fluid dynamics. My research is centred around the analysis of complex systems, and as such, it spans broad interdisciplinary fields -- including dynamical systems, network science, statistics, and data science -- with applications ranging from ecosystem dynamics and neuroscience to climate forecasting and power-grids stability. Overall, I attempt to bridge fundamental mathematical and physical theories with real-world applications, relying heavily on collaborations, mathematics, and data.

My work and research interests (so far) can be grouped under the following topics:

1. nonlinear dynamics and chaos (Applied Mathematics)
2. networks and emergent phenomena (Applied Mathematics)
3. chronobiology and network neuroscience (Mathematical Biology)
4. signal processing and information theory (Data Science)
5. atmospheric physics and fluid instabilities (Applied Physics)
6. power grid stability and stochastic dynamics (Applied Physics)

My aims according to these topics are:

1. Extracting statistical properties (such as the degree of uncertainty, recurrence, predictability, or chaoticity) of non-linear and chaotic systems from finite precision measurements and short signals.
2. In terms of networks, I am interested in characterising complex network structures, for example, by using spectral characteristics, distances, or by community structures, as well as designing methods to infer the underlying network structures from time-series measurements. In terms of emergent phenomena, I seek to understand and forecast collective behaviours (particularly, in relation to the network structure), such as synchronisation, intermittency, chimeras, and chaos.
3. In terms of chronobiology, I am interested in understanding the sleep-wake cycle and its alterations, and understanding how neuronal populations or fireflies can synchronise. In terms of network neuroscience, I am also interested in understanding how neurons and brain regions interconnect (which implies inferring the underlying functional networks from measurements/signals) and how these are altered due to depression, healthy ageing, dementia, and other neurodegenerative diseases.
4. I am interested in developing methods to extract meaningful information from signals (time series and imaging) using theories from non-linear dynamical systems (i.a., symbolic dynamics, sofic shifts, and Markov partitions) and applying them in real-world scenarios (such as to improve polysomnography or for early detection of abnormal neurodegeneration).
5. My interests lie in deriving data-driven models of atmospheric phenomena to improve predictability and developing numerical simulations that can complement experimental set-ups of fluid instabilities.
6. In terms of power grids, I seek to understand how the connectivity (at the transmission level) affects the voltage-angle stability, which is a key aspect of maintaining and returning to equilibrium after a disturbance (given that instability can lead to blackouts with disastrous consequences. I am also interested in finding switch states that optimise the load distribution in islanded hybrid power systems. In terms of stochastic dynamics, I am interested in understanding how the structure of the network interconnecting the components of a stochastic complex system affects its communication and synchronisation, which is relevant in many systems, including power grids, neuronal circuits, surface growth, and stock returns.

Current Research

Selected publications

• Critical parameters of the synchronisation's stability for coupled maps in regular graphs, Chaos, Solitons & Fractals 158, 112001 (2022).

• Low Frequency Oscillations drive EEG's complexity changes during Wakefulness and Sleep, Neuroscience 494, 1-11 (2022).

• The distinct influence of two Madden-Julian's trajectory classes on the South American Dipole, Journal of Climate 35(21), 3487-3501 (2022).

• Small-worldness favours network inference in synthetic neural networks, Nature Scientific Reports 10, 2296 (2020).
  

• Decreased electrocortical temporal complexity distinguishes sleep from wakefulness, Nature Scientific Reports 9, 18457 (2019).

• Entropy-based Generating Markov Partitions for Complex Systems, Chaos: an Interdisciplinary Journal of Nonlinear Science 28(3), 033611 (2018).

• Dynamical detection of network communities, Nature Scientific Reports 6, 25570 (2016).

Past Research

I was a Research Fellow on a Roland Sutton Academic Trust (RSAT) funded project, led by Dr. V. Vuksanovic. The project was focused on developing a model of brain-impaired-functions in Alzheimer’s disease from large-scale brain networks; rather than on existing diagnostic categories. The objective of the overall project is to develop novel neuroimaging-informed ways to classify Alzheimer’s disease and mild cognitive impairment. Neuroimaging-defined networks can be linked to specific behavioural and cognitive scores, which aim to help in early diagnosis.

Collaborations

Ongoing (open-ended)

• Stability analyses of power grids at the transmission level and phase synchronisation: Dr Murilo S. Baptista and Prof Celso Grebogi (ICSMB, University of Aberdeen, U.K.)

• Development of methods for network analysis and characterisation (such as community detection): Dr Marcos G. Quiles and Prof Elbert E. N. Macau (UNIFESP, Brazil), and Dr Juan Gancio (Universitat Politècnica de Catalunya, Spain)

• Development of advanced methods for signal processing: Prof Cristina Masoller and Dr Juan Gancio (Universitat Politécnica de Catalunya, DONLL, Spain), Prof Arturo C. Marti and Dr Cecilia Cabeza (Non-Linear Physics group, Universidad de la República, Uruguay), Dr Murilo S. Baptista and Prof Celso Grebogi (ICSMB, University of Aberdeen, U.K.)

• Analysis of consciousness from EEG and fMRI data of sleep-wake states: Prof Pablo Torterolo (Laboratory of Sleep Neurobiology, Universidad de la República, Uruguay), Dr Diego Mateos (Universidad Autónoma de Entre Ríos, CONICET, Argentina), Dr Claudia Pascovich (Consciousness and Cognition Laboratory, University of Cambridge, U.K.), and Prof Andrés Damián (Molecular Imaging Centre of Uruguay, CUDIM, Uruguay)

• Development of biomarkers for healthy ageing from EEG data (EuroLAD-EEG consortium): Dr Mario A. Parra (Applied Cognition Lab, University of Strathclyde, U.K.)

• Analysis of mice vasculature networks from functional ultrasound data: Dr Javier Brum (Laboratory of Acoustic Ultrasound, Universidad de la República, Uruguay) and Dr Alejandra Kun (Clemente Estable Institute of Biological Research, Uruguay)

• Analysis of brain networks in Alzheimer's disease from functional MRI data: Dr Vesna Vuksanovic (Swansea University Medical Research, UK), Prof Dante Chialvo (Universidad General de San Martín, CONICET, Argentina), and Prof Ignacio Cifre (Universitat Ramon Llull, Spain)

• Analysis of brain networks in depression from functional MRI data: Dr Victoria Gradín (Centre for Basic Research in Psychology, Universidad de la República, Uruguay) and Dr Ignacio Rebollo (DIfE, German Institute of Human Nutrition Potsdam-Rehbrücke)

• Development of climate models and forecast at the intra-seasonal time-scale: Prof. Marcelo Barreiro  and Dr Nicolas Díaz (Department of Atmospheric Sciences, Universidad de la República, Uruguay)

Teaching Responsibilities

Course coordinator for:

• PX2015: Dynamical Phenomena
• PX3014: Energy and Matter
• PX4012: Statistical Physics and Stochastic Systems

Non-course Teaching Responsibilities

• PGT supervision: end-of-term research project for MSc in Data Science students