Dynamics Days Europe 2025

Minisymposia

Call for minisymposia

The call for organizing Minisymposia is opened. Interested organizers may send their proposal to ddeu2025@auth.gr

The proposal should contain

1.  Names, affiliations and contact details of organizers.

2. Title and a short description (one paragraph) for the topic of the proposed minisymposia.

3. A tentative list of potential speakers (names and affiliations).

A minisymposium should have a total duration of 120min. It may have 4 talks of 30 min duration (25 min presentation plus 5 min for questions), but other forms may be suggested as well, e.g. 6 talks of 20 min duration (17  min presentation plus 3 min for questions). A minisymposium may have more than one two-hour session, e.g., part I and part II.

Decision for acceptance / rejection of the proposed minisymposium will be communicated within a week after the proposal is made.

Regarding the submission of the talks in the minisymposium, this is done by invitation of the minisymposia organizers. The submissions are then directed to the minisymposia organizers, who collect them and forward them to the DDE2025 organizers (by email to ddeu2025@auth.gr). The minisymposium organizers may want to suggest to their minisymposium participants to use the abstract template DDE2025 uses for the contributed talks (see Submission web-page). 

All presenters in the minisymposium should be registered (see Registration web-page).

 

List of minisymposia

The following minisymposia will take place in DDE2025. The exact dates/times will be added when the program is announced. Please note that as for now the list of speakers is tentative.

MS1 Session Title: Multistability and Nonlocal Stability Analysis

Session Organisers:
Datseris, George, University of Exeter
email: G.Datseris@exeter.ac.uk
Rossi, Kalel Luiz, University of Oldenburg,
email: kalel.luiz.rossi@uni-oldenburg.de

Several dynamical systems are multistable: they exhibit a coexistence of stable solutions, formally called attractors. Examples include power grids, climate components, the brain, mechanical and metabolic systems, to name a few. Perturbations, such as noise or external shocks, can induce transitions between these attractors – which, depending on the application, may be either desirable or catastrophic. It becomes crucial therefore to study the stability in such multistable systems. Typically stability is studied using local bifurcation analysis and continuation, but this approach can be unsuitable for real-world applications where perturbations are finite-sized instead of infinitesimal. This calls for a nonlocal view of stability. Recent progress has enriched the literature with various quantities that can be used as quantifiers of nonlocal stability: basin stability or volume, the geometry of the basins, basin entropy, return time, minimal fatal shock, and other notions of resilience. In this minisymposium we want to highlight and promote recent research that explores one or several of the following categories:

– novel indicators of nonlocal stability
– novel techniques for finding multiple system attractors and/or their basins of attraction
– nonlocal stability analysis and continuation of multistable systems
– multistability in high-dimensional systems
– very high (10+) or extreme multistability (infinitely many coexisting attractors)
– multistability in chaotic systems

George Datseris – University of Exeter.

Kalel L. Rossi – University of Oldenburg.

Andreas Morr – Potsdam Institute for Climate Impact Research.

Alex Wagemakers – Universidad Rey Juan Carlos.

Muhammed Fadera – University of Exeter.

Arturo C. Marti – Universidad de la Republica.

Dawid Dudkowski – Lodz University of Technology.

Yuanzhao Zhang – Santa Fe Institute.

Andrew Flynn – University College Cork.

Manish Dev Shrimali – Central University of Rajasthan.

MS2 Session Title: Advances in Theoretical and Practical Applications for Infectious Diseases and Control

Session Organisers:
Steindorf, Vanessa, Basque Center for Applied Mathematics, Bilbao, Spain
email: vsteindorf@bcamath.org
Aguiar, Maíra, Basque Center for Applied Mathematics, Bilbao, Spain
email: maguiar@bcamath.org

Focused on future research directions for modeling the spread of pathogens capable of causing new outbreaks, this interdisciplinary symposium aims to promote timely debates exploring various approaches in epidemiology, particularly on the mathematical modeling of infectious respiratory and vector-borne diseases. Key discussions will cover recent advances in mathematical epidemiology, offering a comprehensive look at both theoretical methods and practical applications. Topics will include the role of temporal and spatial dynamics in disease transmission, the challenges of predicting epidemic trends, improving predictive models to inform public health strategies, and the integration of environmental and human behavior factors into models. By bridging theory and practice, the symposium aims to enhance tools for disease control and outbreak preparedness.

1. Vanessa Steindorf
Basque Center for Applied Mathematics, Bilbao, Spain
vsteindorf@bcamath.org
2. Maíra Aguiar
Basque Center for Applied Mathematics, Bilbao, Spain
maguiar@bcamath.org
3. Nico Stollenwerk
Basque Center for Applied Mathematics, Bilbao, Spain
nstollenwerk@bcamath.org
4. Thomas Goetz
University of Koblenz, Koblenz, Germany
goetz@uni-koblenz.de
5. Paula Patrcio
Center for Mathematics and Applications (NOVA Math) and
Department of Mathematics, NOVA FCT, Lisbon, Portugal
pcpr@fct.unl.pt
6. Carlo Estadilla
Bristol Medical School
University of Bristol, Bristol, UK
carlo.estadilla@gmail.com
7. Chiara Cicolani
Universit degli studi dell’ Aquila, L’ Aquilla, Italy
Basque Center for Applied Mathematics, Bilbao, Spain
chiara.cicolani@graduate.univaq.it
8. Akhil K. Srivastav
Basque Center for Applied Mathematics, Bilbao, Spain
asrivastav@bcamath.org

MS3 Session Title: Quantum chaos in few and many body systems

Session Organiser:
Robnik, Marko, CAMTP – Center for Applied Mathematics and Theoretical Physics, University of Maribor, Maribor, Slovenia
email: marko.robnik@guest.um.si

The talks will cover the topics on most recent results in quantum chaos of few and many body systems. We shall address the semiclassical behavior of quantum systems, and their correspondence to the associated classical chaotic systems, as well as the studies of quantum systems without a classical analog. In particular, we shall focus on the following aspects: spectral statistics, phase space localization of eigenstates, the statistical properties of the localization measures, ergodicity properties and their hierarchy, dissipative quantum systems, localization and thermalization, time evolution, in particular studies of OTOC (out-of-time order correlators). Several model systems will be presented and analyzed, on which the phenomenological results are based, as well as they are a basis for theoretical approaches.

Part I (120 min):

1. Giulio Casati, University of Insubria, Como, Italy
2. Marko Robnik, CAMTP, University of Maribor, Slovenia
3. Thomas Guhr, University of Duisburg-Essen, Germany
4. Juan Diego Urbina, University of Regensburg, Germany

Part II (105 min):

1. Matic Orel, CAMTP, University of Maribor (15 min)
2. David Benjamin Villasenor Perez, CAMTP, University of Maribor and UNAM, Mexico (30 min)
3. Qian Wang, CAMTP, University of Maribor and Zhejiang Normal University, Jinhua, China (30 min)
4. Hua Yan, CAMTP, University of Maribor, Slovenia (30 min)

MS4 Session Title: Neural Dynamics Across Spatiotemporal Scales: Models, Learning Processes, Computational Tools, and Clinical Applications

Session Organiser:
Manos, Thanos, ETIS Lab, CY Cergy Paris Université, France
email: thanos.manos@cyu.fr 
Torcini, Alessandro, LPTM, CY Cergy Paris Université, France
email: alessandro.torcini@cyu.fr 
Provata, Astero, Institute of Nanoscience and Nanotechnology, National Center for Scientific Research “Demokritos”, Greece
email: a.provata@inn.demokritos.gr

Neural networks and collective behavior represent leading research frontiers in complex systems theory. The human brain exemplifies a complex neural network, self-organizing into emergent states essential for its functions. Neural activity within individual nodes is often modeled using systems of ordinary differential equations. Such dynamical models offer a theoretical framework to explore the interplay between localized population dynamics and the intricate topology of brain networks, shedding light on overall brain activity. They also account for various forms of plasticity, such as synaptic and structural plasticity, and their influence on the system’s dynamics. This dynamical-modeling approach bridges concepts from mathematics, physics, and dynamical systems theory with empirically observed phenomena. For instance, it establishes connections between attractors, bifurcations, synchronization, and empirical neuroimaging data, including blood-oxygen-level-dependent (BOLD) signals from functional magnetic resonance imaging (fMRI). This mini symposium will feature expert-led discussions on the latest advancements in complex networks, collective behavior, synchronization phenomena, self-organization, neurocomputational platforms, and their diverse clinical applications.

  1. Thanos Manos, ETIS Lab, CY Cergy Paris Université, France
    Email: thanos.manos@cyu.fr
  2. Alessandro Torcini, LPTM, CY Cergy Paris Université, France
    Email: alessandro.torcini@cyu.fr
  3. Astero Provata, Institute of Nanoscience and Nanotechnology, National Center for Scientific Research “Demokritos”, Athens, Greece
    Email: a.provata@inn.demokritos.gr
  4. Viktor Jirsa, Institut de Neurosciences des Systèmes, Aix-Marseille University, France
    Email: viktor.jirsa@univ-amu.fr
  5. Alex Leow, University of Illinois Chicago, USA
    Email: weihliao@uic.edu
  6. Diego Pazo, Instituto de Física de Cantabria, University of Cantabria, Spain
    Email: pazo@ifca.unican.es
  7. Andrey Shilnikov, Neuroscience Institute, Georgia State University
    Email: ashilnikov@gsu.edu
  8. Roberto Barrio, Computational Dynamics Group (CoDy), Departamento de Matemática Aplicada, University of Zaragoza, Spain
    Email: rbarrio@unizar.es
  9. Simona Olmi, Institute for Complex Systems, Florence, Italy
    Email: simona.olmi@gmail.com
  10. Johanne Hizanidis, Institute of Electronic Structure & Laser (IESL/FORTH)
    Email: hizanidis@physics.uoc.gr
  11. Jeroen van Schependom, AIMS lab, Center for Neurosciences, Vrije Universiteit Brussel, Belgium.
    Email: jeroen.van.schependom@vub.be
  12. Oleh Omel’chenko, Department of Physics and Astronomy, University of Potsdam, Germany
    Email: oleh.omelchenko@uni-potsdam.de
  13. Sandra Diaz-Pier, Jülich Supercomputing Centre, Forschungszentrum Jülich, Germany
    Email: s.diaz@fz-juelich.de
  14. Klaus Lehnertz, Neurophysics Group, Department of Epileptology, Medical Center, University of Bonn, Germany
    Email: Klaus.Lehnertz@ukbonn.de
  15. Raphael Bergoin, University Medical Center Hamburg-Eppendorf, Germany
    Email: raphael.bergoin@gmail.com
  16. Pau Clusella Coberó, Department of Mathematics, Universitat Politècnica de Catalunya
    Email: pau.clusella@upc.edu

MS5 Session Title: Applications of ordinal patterns-based complexity quantifiers for experimental time-series

Session Organiser:
Pattanayak, Arjendu K., Department of Physics and Astronomy, Carleton College, Northfield, USA
email: arjendu@carleton.edu 
Aragoneses, Andrés, Physics Faculty, Whitman College, Walla Walla, USA
email: aragonea@whitman.edu

Recent advances in time-series analysis have highlighted the value of ordinal patterns-based complexity quantifiers as robust tools for understanding dynamical systems. These measures, based on permutation entropy and other metrics applied to symbolic analysis of the time-series, provide a computationally efficient means of uncovering hidden patterns, underlying temporal symmetries, and regime changes in experimental data. Applications span diverse fields such as neuroscience, climatology, finance, quantum chaos, and photonics, including the characterization of time-series regularity, detection of transitions in complex systems, and classification of families of chaos.

In this mini-symposium we want to bring together researchers to explore the breadth of applications for these methods from across the fields listed above. Topics include, but are not limited to, the characterization of time-series regularity, detection of transitions in complex systems, and quantification of complex dynamics.

By focusing on both theoretical advancements and real-world implementations, this symposium aims to foster interdisciplinary dialogue and stimulate innovation in the analysis of experimental time-series data.

Juan Gancio (juan.gancio@upc.edu)
Jordi Tiana-Alsina (jordi.tiana@ub.edu)
Cristina Masoller (cristina.masoller@upc.edu)
Giulio Tirabassi (giulio.tirabassi@udg.edu)
María Duque (maria.duque@upc.edu)
Miguel C. Soriano (miguel@ifisc.uib-csic.es)
Xavier Porte (javier.porte-parera@strath.ac.uk)
Inmaculada Leyva (inmaculada.leyva@urjc.es)
Juan A. Almendral (juan.almendral@urjc.es)

MS6 Session Title: Patterns of synchrony and asynchrony in oscillatory media and networks

Session Organiser:
Pikovsky, Arkady, Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany,
email: arkady.pikovsky@gmail.com

Nepomnyashchy, Alexander, Department of Mathematics, Technion – Israel Institute of Technology, Haifa, Israel,
email: nepom@technion.ac.il

It is known that the same nonlinear system can perform synchronous oscillations or display asynchronous or disordered behavior, depending on some delicate differences in parameters and conditions. The synchronization can happen despite a disorder within the system, while synchronous oscillations can be spontaneously destroyed by internal instabilities. The synchronous and disordered dynamics can coexist. The goal of the minisymposium is to present the panorama of phenomena related to synchronization and desynchronization in networks of oscillators and oscillatory media, and elucidate their common features and dynamic patterns.

Part I

Arkady Pikovsky, Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany.
arkady.pikovsky@gmail.com

Simona Olmi, Institute of Complex Systems, CNR in Sesto Fiorentino, Florence, Italy,
simona.olmi@fi,isc.cnr.it

Rok Cestnik, Center for Mathematical Sciences, Lund University, Lund, Sweden.
rok.cestnik@math.lth.se

Oleh Omelchenko, Institute of Physics and Astronomy, University of Potsdam, Potsdam, Germany,
oleh.omelchenko@uni-potsdam.de

Part 2

Dmitry Turaev, Dynam IC, Imperial College London, London, UK, d.turaev@imperial.ac.il

Idan Sorin, Department of Mathematics, Technion – Israel Institute of Technology, Haifa, Israel,
idansorin@campus.technion.ac.il

Astero Provata, Institute of Nanoscience and Nanotechnology, National Center for Scientific
Research “Demokritos”, Athens, Greece, a.provata@inn.demokritos.gr

Seungjae Lee, Chair for Network Dynamics, Technical University of Dresden, Dresden, Germany,
seungjae.lee@tu-dresden.de

MS7 Session Title: Recent trends in dynamical chaos: from theory to applications

Session Organiser:
Kazakov, Alexey, University Higher School of Economics, Nizhny Novgorod, Russia
email: kazakovdz@yandex.ru

Turaev, Dmitry, Imperial College London, London, UK
email: dturaev@imperial.ac.uk

Sinelshchikov, Dmitry, 
Biofisika Institute (CSIC-UPV/EHU), Leioa, Spain
email: disine@gmail.com

The minisymposium is devoted to modern aspects and trends in the theory of dynamical chaos, with focus on higher-dimensional problems. It will cover various topics: dissipative chaos, reversible systems, and Hamiltonian dynamics, theory of local and global bifurcations, theory of pseudohyperbolic, hyperchaotic, and spiral attractors, as well as applications.

1. Dongchen Li
Shanghai University, China
d.li@imperial.ac.uk
2. Arturo Vieiro
Barcelona University, Spain
vieiro@maia.ub.es
3. Ainoa Murillo
Barcelona University, Spain
amurillo@ub.edu
4. Alexey Kazakov
HSE University, Nizhny Novgorod, Russia
kazakovdz@yandex.ru
5. Dmitry Sinelshchikov
Biofisika Institute (CSIC-UPV/EHU), Leioa, Spain
disine@gmail.com
6. Efrosiniia Karatetskaia
HSE University, Nizhny Novgorod, Russia
eyukaratetskaya@gmail.com
7. Klim Safonov
HSE University, Nizhny Novgorod, Russia
safonov.klim@yandex.ru
8. Vyacheslav Kruglov
Carl von Ossietzky University of Oldenburg, Germany
kruglovyacheslav@gmail.com

MS8 Session Title: Dynamics of physiological networks: from function to malfunction

Session Organiser:
Schöll, Eckehard, Institute for Theoretical Physics, Technische Universität Berlin, Berlin, Germany 
email: schoell@physik.tu-berlin.de

Andrzejak, Ralph Gregor, Department of Information and Communication Technologies, Universitat Pompeu Fabra, Barcelona, Spain
email: ralph.andrzejak@upf.edu

In the human organism, multi-component physiological systems, each with its own regulatory mechanism, continuously interact to coordinate their functions in an integrated network. The dynamics resulting from these interactions exhibits emergent patterns of synchronization or desynchronization which are associated with healthy or pathological states. Examples include tumor dynamics in physiological multilayer networks of organs and the immune system; brain network dynamics; psychiatric interactions of consciousness and decision making, among others. Often phase transitions and critical phenomena occur in such dynamical networks, leading to a plethora of partial synchronization patterns and complex collective behavior.

1. Frederico Costa
Oncology Department, Hospital Sírio Libanês, São Paulo, Brazil
2. Deniz Eroglu
Faculty of Engineering and Natural Sciences, Kadir Has University, 34083 Istanbul, Turkey
Department of Mathematics, Imperial College London, London SW7 2AZ, United Kingdom
3. Simona Olmi
CNR-Consiglio Nazionale delle Ricerche—Istituto dei Sistemi Complessi, Sesto Fiorentino, Italy
4. Günter Schiepek
Institute of Synergetics and Psychotherapy Research, Paracelsus Medical University, Salzburg, Austria
University Hospital of Psychiatry, Psychotherapy and Psychosomatics, Paracelsus Medical University, Salzburg, Austria
Faculty of Psychology and Educational Sciences, Ludwig Maximilians University, Munich, Germany

MS9 Session Title: Advances in the theoretical understanding and hardware implementations of reservoir computers

Session Organiser:
Flynn, Andrew, School of Mathematical Sciences, University College Cork, Cork, Ireland
email: andrewflynn@ucc.ie

Hizanidis, Johanne, Institute of Electronic Structure and Laser, Foundation for Research and Technology-Hellas, Heraklion, Greece
email: hizanidis@physics.uoc.gr 

Lüdge, Kathy, Institute of Physics, Technische Universität Ilmenau, Ilmenau, Germany
email: kathy.luedge@tu-ilmenau.de

Parlitz, Ulrich, Biomedical Physics Group, Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
email: ulrich.parlitz@ds.mpg.de

Reservoir computing leverages the response of driven dynamic systems for data-driven modeling, time-series prediction, classification, and control. Historically, recurrent neural networks have primarily served as dynamic reservoirs, but recent developments have extended this general approach to a variety of substrates, including passive and active optical systems, electro-optical systems, magnetic systems, memristors, spin wave systems, swarms, skyrmion textures, biological tissue, and quantum systems. A common goal of these investigations is to improve our theoretical understanding of various reservoir computing approaches and to achieve fast and energy-efficient hardware implementations. This minisymposium brings together experts across these areas to foster new ideas and cooperations which is vital towards advancing reservoir computing.

1. Lina Jaurigue (Technische Universität Ilmenau, Germany), lina.jaurigue@tu-ilmenau.de
2. Ulrich Parlitz (Max Planck Institut for Dynamics and Self-Organization, Göttingen, Germany), ulrich.parlitz@ds.mpg.de
3. Hiromichi Suetani (Oita University, Japan), hsue@icloud.com
4. Christoph Räth (DLR München, Germany),5. christoph.raeth@dlr.de
5. Martin Trefzer (University of York, UK), martin.trefzer@york.ac.uk
6. Miquel C. Soriano (Campus Universitat de les Illes Balears, IFISC, Mallorca, Spain) , miguel@ifisc.uibcsic.es
7. Andrew Flynn (University College Cork, Ireland), andrewflynn@ucc.ie
8. Kathy Lüdge (Technische Universität Ilmenau, Germany), kathy.luedge@tu-ilmenau.de
9. Guy van der Sande (VUB Brussels, Belgium), guy.van.der.sande@vub.be

MS10 Session Title: Dynamical Systems meets Machine Learning

Session Organisers:
Nieters, Pascal, Institute of Cognitive Science, University of Osnabrück, Osnabrück, Germany
email: pascal.nieters@uni-osnabrueck.de

Vortmeyer-Kley, Rahel, Institute for Chemistry and Biology of Marine Environment, Carl von Ossietzky Universität Oldenburg, Oldenburg, Germany
email: rahel.vortmeyer-kley@uni-oldenburg.de  

Machine learning tools have rapidly become integral to the analysis of data from dynamical systems, offering new perspectives on data-driven model development. While classical, theory-driven approaches may rely on simplifying assumptions, purely data-driven methods risk overfitting and can fail to illuminate understanding of the underlying dynamical relationships. Hybrid methods that integrate theoretical knowledge with data-driven components promise a new class of models and open opportunities for automation in the process of scientific discovery. Yet questions persist about how to interpret these models: Do they reveal or obscure key interactions and dynamics compared to more traditional approaches? And what is the scientist’s role in shaping and understanding such frameworks? This minisymposium invites contributions from across the sciences that employ machine learning and AI to identify relationships among dynamic variables and forecast future behavior. We welcome both theoretical and applied work, with the goal of fostering an interdisciplinary dialogue on the benefits, limitations, and emerging opportunities of machine learning for dynamical systems and real-world modeling applications.

1. Pascal Nieters, Institute of Cognitive Science, University of Osnabrück/ Rahel Vortmeyer-Kley, Institute for Chemistry and Biology of Marine Environment, Carl von Ossietzky Universität Oldenburg
(Navigating to the right solution when learning bifurcating dynamical systems)

2. Gianmarco Ducci, Fritz-Haber-Institut der Max-Planck-Gesellschaft Berlin
(A robust approach for sparse parametric data driven modeling)

3. Lukas Stelz, FIAS, University Frankfurt
(Inferring Local Transmission Networks from Epidemiological Incidence Data)

4. Sedighe Raeisi, Institute of Cognitive Science, University of Osnabrück
(Computational discovery of individual differences in cognitive mechanisms)

2025 - Dynamics Days Europe 2025
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