External Collaborators

Prof. Andreou Christina  (Lubeck University, Germany)

Prof. Antonopoulos Christos  (Essex University, UK)

Prof. Mandilara Aikaterini   (Nazarbayev University, Kazakhstan)

Prof. Schoell  Eckehard(Technical Universitaet of Berlin, Germany)

Prof. Vlamos Takis  (Ionian University, Greece)

PhD Students

Kasimatis Theodoros

Tsigkri Nefeli-Dimitra

MSc Students

Rontogiannis Alexandros

Previous Students & Postdocs

Argyropoulos George (MSc, 2017-2020)

Koulierakis Ioannis (MSc, 2017-2020)

Karakos George (MSc 2017-2019)

Labrakos Christos (MSc, 2017-2018)

Georgiou Antoine (BSc, 2015-2016)

Thanos Dimitrios (BSc, 2015-2018)

Kasimatis Theodoros (MA 2014-2016)

Tsigkri Nefeli-Dimitra (MA 2013-2015)

Dr. Hizanidis Johanne  (Postdoc, 2013-2017)

Flokas Lambros (BA 2015)

Mousa George (BSc 2016)

Theodoropoulos Spyros (BSc 2016)

Breki Christina-Marina (BA 2014-2015)

Dr. Bassett Jason  (BSc, 2012-2013)

Vogiatzian Philippos-Arthuros  (BSc, 2012-2013)

Dr. Kovanis Michail  (BSc, 2012)

Dr. Katsaloulis Panayotis  (MSc, 2006-2007, PhD, 2007-2011)

Dr. Kouvaris Nikos  (PhD, 2007-2011)

Dr. Noussiou Vicky  (PhD, 2004-2009)

Prof. Oikonomou Thomas  (PhD, 2004-2008)

Dr. Rabias Ioannis  (Postdoc, 2002)

Dr. Sfyrakis Kostas  (Postdoc, 2002-2003)

Prof. Langlois Cyril  (DEA, 2001)

Dr. Prassas Vassilios  (MSc, 1998)

Dr. Chantron Arnaud  (DEA, 1999)

Prof. Kalosakas George  (Postdoc, 2001)

Prof. Shabunin Alexey  (Postdoc, 1999,2001,2003,2007)

Prof. Chichigina Olga  (Postdoc, 2004)

Chondrou Presveia  (MSc 2003-2004)

Dr. Tsekouras Georgios-Artemios  (PhD, 2000-2004)

Statistical Mechanics & Dynamical Systems Laboratory

The Laboratory of Statistical Mechanics and Dynamical Systems (STAT-DYN) was founded in 02/2004 as part of the Institute of Physical Chemistry, while from 2014 belongs to the Institute of Nanoscience and Nanotechnology. Its research focuses on the fields of :

    1. Non-linear Dynamics
    2. Statistical Mechanics
    3. Networks of Interacting Neurons
    4. Computational Neuroscience
    5. Brain Dynamics
    6. Complex Networks
    7. Reaction Diffusion Systems
    8. Fractals

Reaction-Diffusion process taking place on a 3D fractal network







 Movies in



Chimera states on a 2D network


Brain frequency spectrum & corresponding chimera state

Our aim is the development of methods and models for understanding the emergence and evolution of mesoscopic and macroscopic spatial patterns and temporal synchronization motifs due to the interactions between nonlinear elements (e.g., neuronal oscillators or population dynamics models). The spatiotemporal structures induced by the interacting units include chimera states in neural networks, aggregates, spirals and stripe formations in reaction- diffusion systems, helices, fractals, synchronisation phenomena etc. which can be experimentally observed in material science, physics, chemistry and biology.

Our studies in particular include research on fractal pattern formation and correlations near critical points but also research in open systems, dissipative in constant exchange with the environment.

  • Away from the critical points in closed, isolated, conservative  systems short range correlations and spatiotemporal patterns with well-defined length and time scales are studied (eg. spiral and stripe formations, helices etc.).
  • At the critical points long range correlations are developed and information exchanges are studied at the long scales.
  • In open, coupled dissipative systems the reduction of the phase space is studied, which leads to unexpected spatiotemporal phenomena such as the chimera states in coupled neuronal networks.

The understanding of these structures at the micro-, meso- and macro scales and the interaction between these three levels of description has major technological impact in materials science and physical, chemical and biological processes.

For the study of complex systems in the lab we develop a) statistical methods and algorithms describing the evolution of complex morphologies and b) modelling tools for the dynamics of pattern formation and synchronization phenomena. Statistical methods include thermodynamic approaches, entropic (extensive and non-extensive) approaches, theory of complex networks, theory of long and short range distributions, Levi distributions, theory of random walks. For the study of the mechanisms creating complex patterns, non-linear dynamical systems of hierarchical complexity are used, together with mean-field theories, exact enumeration methods, real space renormalisation theory, theory of stochastic processes and numerical integration and kinetic Monte Carlo Methods.

Applications include, among others:

  • Numerical Simulations of Brain Dynamics
  • Comparison of dynamics between healthy brains and brains with neurodegenerative disorders.
  • Recording and modelling of the complex fractal architecture of the neuron axons spanning the human brain
  • Reaction-diffusion processes on complex networks
  • Studies of surface phenomena and aggregates with fractal morphology,
  • Bioinformatics
  • Statistical analysis and modelling of biological tissues and macromolecules,


Group Photos

Group Photos 2017





Group Photos 2016




Group Photos 2015