My research focus on Computational Science & Engineering and in particular the development
and implementation of computational methods for the analysis of
Nonlinear/ Complex systems. There are four directions in this effort to
analyze/engineer Large-Scale/ Complex Systems:
(A) Modelling and Simulation
(B) Development and implementation of computational methods
(C) Control algorithms
(D) Linking the above with Machine and Manifold Learning algorithms.
strive to address emerging interdisciplinary challenging Complex
problems with an empahsis in Computational Neuroscience but also Complex Social Networks and their Dynamics, Mathematical Epidemiology, Fluid Mechanics, Materials Science, Environmental
Modelling and Management, Process Engineering, Economics and Finance, and Seismology in collaboration with strong and interested colleagues.
The scientific keystones of
the research integrates recent advances mainly from: Systems Dynamics, Complex systems Modeling, Statistical Mechanics, Numerical Bifurcation
theory, Numerical Analysis of larfe-Scale Systems, Complex Networks and Control theory.
Simulation of Complex Systems
For many problems of contemporary practical
and research interest in Applied Mathematics, Engineering and Physical
Sciences, the closures required to formulate good models in the
not available. Most of them are inherently multi-scale ( interactions
of neurons and groups of neurons on complex brain networks, chemical
reactions and mass-transfer phenomena on catalytic surfaces, liquid crystals dynamics, emergence and dynamics of collective phenomena in social systems, evolution of epidemics, the dynamics of fire spread in heterogeneous environments,, dynamics
My research interest here focuses
on the development of microscopic/ individualistic stochastic models using
Agent-based, Brownian Dynamics, Molecular Dynamics, Monte-Carlo and Cellular
Automata simulation techniques for complex dynamical problems arising across
disciplines with important engineering, health, social and environmental implications.
I am also interested in
studying the influence of the topology of complex networks on the emergent
dynamics of dynamical systems. The dynamic effects of network heterogeneity are central to fundamental problems
in Computational Neuroscience, Biological Systems, Materials Science, Epidemics, Information Exchange and Social collective phenomena including Economics and Finance. Towards
this aim, the efforts are also focused on the development of computational algorithms for
constructing topologies of networks with prescribed characteristics that are
able to approximate real-world network structures.
Machine and Manifold Learning Techniques for Systems
Identification and Signal Processing
The aim is mainly focused in Computaional Neuroscience for the modelling and analysis
of Brain activity
as recorded from fMRI, EEG, MEG as coupled with behavioural data
(phenotypes) to study the mechanisms that pertain to the cognitive
mechanisms of decision making, working memory and the identification of "biomarkers" of neurological disorders such as Schizophrenia and Epilepsy. Rsearch efforts are focused on the construction of the underlying effective and Functional Connectivity Networks.
Computational Analysis of
Large-Scale and Complex Systems
I am interested in studying complex
problems for which coarse-grained evolution equation models can be in principle
derived in the form of Ordinary or
Partial Differential Equations, however, due to inherent complexity, such
models are not explicitly available in a closed form.
My research focuses on the
bridging between microscopic/individual-based problem descriptions and
state-of-the-art computational methods, in order to provide a systematic
approach for analyzing the parametric behaviour of complex/ multi-scale
The idea is based on the
Equation-Free framework that bypasses the explicit derivation of closures for
the emergent-level equations. Steady state and time-dependent computations,
stability computations, as well as continuation and numerical bifurcation
analysis and other important tasks such as the computational analysis and
continuation of self-similar solutions and rare-events analysis of the
complex-emergent dynamics can be performed in a straightforward manner.
Nonlinear Dynamics, Computational
Analysis and Control
The interface between Bifurcation
theory and Control
is an active research area. Both disciplines share the
goal of accurately locating and efficiently converging on (i.e.
stabilizing) steady states computationally or experimentally.
I aim at developing numerical approaches at the trijunction of Computational Bifurcation analysis, Complex Systems and Control theory
experiments and Large-Scale/ Complex problems as these can be principally described by
ordinary or partial differential equations.
The efforts are mainly
(a) on the adaptive detection of instabilities for experiments and large scale
and complex systems, motivated from numerical bifurcation
algorithms for critical point detection
(b) address the development of
feedback control schemes, which, can be implemented as a shell around
experiments and/or existing microscopic/stochastic simulators, and generally
large-scale systems, to enable them to automatically trace their
The above directions of research involve extensive collaboration with several interested colleaques including (currently):
Professor Yannis Kevrekidis, Princeton
Dr. Bill Gear, Princeton University, USA,
Professor Eleftherios Mylonakis, Medical School, Brown University, USA
Professor Nikos Smyrnis, Medical School, University of Athens, Greece,
Professor Lieven Lagae, Medical School, Section
Paediatric Neurology, K.U.Leuven, Belgium,
Gerasimos Papadopoulos, Institute of Geodynamics, National Observatory of Athens, Greece
Dr. Lucia Russo, Combustion Institute of the C.N.R., Naples, Italy
Professor Paola Russo, Dept.
of Chemical Materials and Environmental Engineering, Sapienza University of
Professor Yannick de Decker, Center for Nonlinear Phenomena and Complex
Systems, UniversitÚ Libre de Bruxelles, Belgium,
Professor Dimitris Maroudas, University of Massachusetts, Amherst, USA
Professor George Georgiou, Dept. of Mathematics and Statistics, University of Cyprus,
Professor Marissa di Matteo, Dept. of Industrial Engineering, University of Salerno, Italy,
Professor Dr. Bj÷rn Reineking, National
Institute for Environmental Science and Research at Grenoble, France,
Professor Silvestro Crescitelli, Dept. of Materials Science and Engineering, University of Naples Federico II, Italy,
Professor Dietmar Janetzko, Cologne Business School, Germany
Professor Antonis Zagaris, Dept. Applied Mathematics, University of Twente, The Netherlands