Overview
I work in the fields statistical mechanics and complexity and networks with an emphasis on far from equilibrium phenomena. The science of complexity is highly interdisciplinary and often deals with dynamical systems composed of many interacting units, for example organisms in biology, heart mucle cells in the myocardium, grains in granular media, network of agents in economics etc. Methods from statistical mechanics are emplyed to gain insight into the behaviour of such systems.
The overall objective of the science of complexity is to address why Nature is complex, not simple as the laws of physics seem to imply. How, for example, can scale invariance and organisation emerge from simple underlying rules associated with the individual units? In this sense, complexity refers to the emergent behaviour that arises from the repeated application of simple rules in systems with many degrees of freedom.
Keywords: Statistical mechanics, complexity, non-equilibrium systems, emergent properties, scale invariance, fractals, self-organised criticality, granular systems, ricepiles, stick-slip behaviour, spring-block models, relaxation processes, avalanches, earthquakes, rain, evolution, and atrial fibrillation.
Collaborators
Max Falkenberg, Department of Mathematics, City University, Cardiology: Modelling Atrial Fibrillation, Network Science, 2017
Tim Evans, Department of Physics, Imperial College London, Complexity & Networds Science, 2017
Deepak Dhar, Indian Institute of Science Education and Research, Pune, Self-organised criticality, 2015
Prof. Nicholas S. Peters, Faculty of Medicine, Dept. of Cardiology, Imperial College London, Cardiology: Modelling atrial fibrillarion, 2011
Paul Expert, University College London, Neuroscience, brain dynamics, brain fMRI, 2009
F Turkheimer, Center for Neuroscience, Dept. of Medicine, Imperial College London, Neuroscience, brain dynamics, brain fMRI, 2008
D Chialvo, Professor, David Geffen School of Medicine, University of California, Los Angeles (UCLA), Neuroscience, brain dynamics, brain fMRI, 2008
Elsa Arcaute, University College London, Self-regulatory systems. Ant colonies as complex systems., 2008
AB Sendova-Franks, Reader in biometry and animal behaviour, Dept. of Engineering & Mathematics, University of the West of England, Self-regulary social systems. Ant colonies as complex systems., 2006
A Espinosa, computer and systems engineer, Business school, Hull University, Viable social systems. Management systems., 2006
N Franks, Professor of animal behaviour and ecology, School of biological sciences, University of Bristol, Self-regulatory systems. Ant colonies as complex systems., 2006
Ole Peters, London Mathematical Laboratory, Self-organized criticality and critical phenomena in atmospheric precipitation, 2002
Leon Danon, University of Bristol, Unified scaling law for earthquakes, 2000
Peter CW Holdsworth, Ecole Normale Supérieure de Lyon, Universal fluctuations in correlated systems, 1999
Kim Sneppen, Niels Bohr Institute, University of Copenhagen, Network Science, 1997
Anders Malthe-Soerenssen, Department of Physics, University of Oslo, Dynamics of slowly driven granular media, 1995
Jens Feder, Department of Physics, University of Oslo, Dynamics in slowly driven granular systems, 1993
Per Bak, Self-organised criticality, 1990
HJ Jensen, Professor of Mathematical Physics, Dept. of Mathematics, Imperial College London, Self-organised criticality, biological evolution, dynamical systems, complexity and network science, brain dynamics, musical creativity, 1988
Vera Pancaldi, University of Toulouse, Statistical Physics: Reservoir engineering
Research Student Supervision
Chen,B, Yi-Er-San topics in network science: centrality, bicycle, triplet
Ciacci,A, Stories from different worlds in the universe of complex systems
Clough,J, Causal structure in networks
Collobiano,SAD, Tangled Nature: A model of ecological evolution
Expert,P, An Odyssey with complexity and network science: From the brain to social systems
Falkenberg,M, Studies in Complex Systems: Complex Networks with Hidden Layers & Modelling Atrial Fibrillatio
Farid,N, On the dynamics and topology of networks
Manani,K, Structure and dynamics in atrial fibrillation: A model of cardiac excitation
Moloney,NR, Numerical investigations into order parameter fluctuations
Pancaldi,V, Coarse graining equations for flow in porous media: A Haar wavelets and renormalization approach
Peters,DOB, Approaches to criticality: Rainfall and other relaxation processes
Rahman,S, The neuroscience of musical creativity using complexity tool
Razak,F, Mutual information based measures on complex interdependent networks of neuro data sets
Stapleton,M, Self-organised criticality and non-equilibrium statistical mechanics
Yao,Q, Different roles of nodes in networks
Zachariou,N, A complexity and networks approach to sustainability