Marius Yamakou

Prof. Dr. Marius Yamakou

Interim Professor

Faculty of Sciences
Department of Data Science (DDS)

Room: Room 02.343
Cauerstr. 11
91058 Erlangen

Assistance

Andrea Hoppe

Cauerstr. 11
91058 Erlangen
More › Details for Andrea Hoppe

Office hours: By appointment via e-mail or on Fridays, 11:30 am – 12:30 pm, Room: 02.343

  • 04/2021 –  present: Researcher and Lecturer, Department of Data Science, University of Erlangen-Nürnberg
  • 10/2024 – 03/2025: Interim Professor, Department of Data Science, University of Erlangen-Nürnberg
  • 11/2019 – 03/2021: Postdoc, Department of Mathematics, University of Erlangen-Nürnberg, Germany
  • 02/2018 – 10/2019: Postdoc, Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany

  • 24/03/2025 – 05/04/2025: INRIA Research Centre, University of Montpellier, France
  • 18/08/2024 – 27/08/2024: Centre for Mathematical Sciences, Lund University, Sweden
  • 28/05/2023 – 03/06/2023: Centre for Mathematical Sciences, Lund University, Sweden
  • 12/02/2023 – 23/02/2023: Perimeter Institute for Theoretical Physics, Waterloo, Canada
  • 05/12/2022 – 18/12/2022: Department of Mathematics, Brandeis University, Massachusetts, USA
  • 01/10/2022 – 30/10/2022: INRIA Research Centre, Université Côte d’Azur, France
  • 01/02/2019 – 30/04/2019: Department of Applied Mathematics, Technical University of Denmark, Denmark

  • 10/2014 – 02/2018: IMPRS Scholarship, Max Planck Institute for Mathematics in the Sciences, Leipzig
  • 04/2021 – 03/2023: DFG Research Grant as Principal Investigator (Project No. 456989199),  ∼ € 200K

  • 04/2020 – present: Departments of Mathematics and Data Science, University of Erlangen-Nürnberg
    • Lecture and exercise classes: Theory of Neural Dynamics and Applications to Machine Learning, SS 25
    • Lecture: Selected Topics in Mathematics of Learning, WS 24/25
    • Lecture and exercise classes: Dynamical System Theory for Data Scientists, WS 24/25
    • Lecture and exercise classes: Theory of Neural Dynamics and Applications to Machine Learning, SS 24
    • Lecture and exercise classes: Dynamical System Theory for Data Scientists, WS 23/24
    • Lecture and exercise classes: Theory of Neural Dynamics and Applications to Machine Learning, SS 23
    • Exercise classes: Mathematics for Engineers: Stochastics, SS 20
  • 02/2019 – 04/2019: Department of Applied Mathematics, Technical University of Denmark
    • Lecture and exercise classes: Dynamical Systems 2 (M.Sc. course)
  • 10/2016 – 10/2017: Max Planck Institute for Mathematics in the Sciences, Leipzig
    • Seminar lecture series: 5 lectures on Stochastic Neural Dynamics
  • 10/2012 – 06/2013: Department of Physics, University of Buea
    • Exercise classes: PHY 202: Newtonian Mechanics
    • Exercise classes: PHY 207: Mathematical Methods for Physics 1
    • Exercise classes: PHY 301: Analytical Mechanics
    • Exercise classes: PHY 306: Mathematical Methods for Physics 2

I’m happy to discuss potential bachelor’s and publishable master’s thesis topics at the intersection of dynamical systems theory, mathematical/computational neuroscience, machine learning, and data science.

  • 2025 – present: Dua Kasvi, Predicting bursting dynamics in Morris-Lecar neurons with reservoir computing
  • 2025 – present: Alina Schlabritz, Optimization of noise-induced resonances on simplicial complexes: Application in computational neuroscience
  • 2025 – present: Divyesh Savaliya,  Self-induced stochastic resonance problem: A physics-informed neural network approach
  • 2025 – present: Behnam Babaeian, Chaotic dynamics, synchronization, and Hamiltonian analysis of neurons using physics-informed machine learning
  • 11/2024 – present: Pooya Khalaji, Chaos-induced inhibition of spiking activity in adaptive neural networks: Numerical simulations and data analysis
  • 03/2024 – 08/2024: Jay Asodariya, Motion estimation and magnification using swin V2 image transformer and deep convolutional neural networks
  • 10/2023 – 05/2024: Jan Kobiolka, Reduced-order adaptive synchronization in a chaotic neural network with parameter uncertainty: A dynamical system vs. machine learning approach
  • 04/2020 – 04/2021: Florian Bönsel, Control of noise-induced coherent oscillations in three-neuron motifs
  • 03/2016 – 02/2017: Gregor Schuldt, Analyse des Morris-Lecar-Neuronenmodells mit stochastischen Störungen

  • 10/2024 – present: Jonas Sengfelder, Chaotic synchronization in non-identical neural networks

  • 04/2025: Mathematical Neuroscience Seminar, INRIA Research Center, University of Montpellier, France
  • 03/2025: Lecture at the FAU Research Training Group FRASCAL on Machine Learning & Neural Networks, FAU Erlangen
  • 10/2024: Biointerfaces Seminar,  Laboratory of Biointerfaces, Dept. of Chemistry and Pharmacy, FAU, Erlangen
  • 08/2024: International Workshop on Network Dynamics, Centre for Mathematical Sciences, Lund University, Sweden
  • 07/2024: International Conference – XLIV Dynamics Days Europe, Bremen, Germany
  • 06/2024: International Conference on Mathematical Neuroscience, University College Dublin, Ireland
  • 11/2023: Workshop: Dynamics in Coupled Networks, Weierstrass Institute for Applied Analysis & Stochastics, Berlin
  • 10/2023: Computational Neuroscience Seminar: University College London (UCL), London, United Kingdom
  • 07/2023: 32nd Annual Meeting, Organization for Computational Neurosciences, Leipzig, Germany
  • 06/2023: Dynamical Systems Seminar, Centre for Mathematical Sciences, Lund University, Sweden
  • 05/2023: Seminar of Statistical Learning and Dynamical Systems, ScaDS.AI Institute, Uni. of Leipzig, Germany
  • 05/2023: SIAM Conference on Applications of Dynamical Systems, Portland, Oregon, USA
  • 03/2023: Dynamical Systems Seminar, Max Planck Institute for Mathematics in the Sciences, Leipzig, Germany
  • 02/2023: Dynamical systems seminar, Department of Applied Mathematics, University of Waterloo, Canada
  • 02/2023: 14th Conference on Dynamical Systems Applied to Biology and Natural Sciences, Bilbao, Spain
  • 12/2023: Dynamical Systems in Neuroscience seminar, Brandeis University, Waltham, Massachusetts, USA
  • 11/2022: International Conference  Control of Self-Organizing Nonlinear Systems, Potsdam, Germany
  • 10/2022: Conference on Complex Systems, Palma de Mallorca, Spain
  • 09/2022: Workshop on Control of Self-Organizing Nonlinear Systems, Wittenberg, Germany
  • 06/2022: 7th International Conference on Random Dynamical Systems, Hanoi, Vietnam
  • 05/2022: Nonlinear Dynamics Seminar,  Weierstrass Institute for Applied Analysis and Stochastics, Berlin, Germany
  • 09/2021: International Conference on Stochastic Resonance, Perugia, Italy
  • 05/2021: SIAM Conference on Applications of Dynamical Systems, Portland, USA
  • 11/2020: Mini-workshop on Neuronal Dynamics, University of Erlangen-Nürnberg, Germany
  • 08/2020: XL. Dynamics Days Europe, Nice, France
  • 02/2020: Oberseminar: Dynamics, Department of Mathematics, Technical University of Munich, Germany
  • 09/2019: 15th Seminar on Stochastic and Collective Effects in Neural Systems, University of Granada, Spain
  • 07/2019: Workshop on Oscillations, Transients, and Fluctuations in Complex Networks, University of Copenhagen
  • 09/2018: Bernstein Conference on Computational Neuroscience, Technical University of Berlin, Germany
  • 07/2018: 27th Annual Meeting, Organization for Computational Neurosciences, Seattle, USA
  • 05/2018: Seminar: Dynamics and Control of Complex Networks, Inst. of Theoretical Physics, Technical University of Berlin
  • 06/2018: 4th International Conference on Mathematical Neuroscience, Juan-les-Pins, France
  • 03/2018: Deutsche Physikalische Gesellschaft (DPG) Spring Meeting, Berlin, Germany
  • 09/2017: Bernstein Conference on Computational Neuroscience, University of Göttingen, Germany
  • 05/2017: SIAM Conference on Applications of Dynamical Systems, Snowbird, Utah, USA
  • 11/2016: 3rd Dresden-Leipzig Dynamics Day, Technical University of Dresden, Dresden, Germany
  • 06/2015: Workshop: Dynamics of Multi-Level Systems, Max Planck Institute for Physics of Complex Systems, Dresden

My research lies at the intersection of applied mathematics, theoretical physics, computational neuroscience, data science, and machine learning. I focus on bridging the gap between mathematical theory and real-world applications, leveraging machine learning to develop innovative tools for analyzing and controlling complex dynamical systems. A central goal is to advance data-driven modeling and discover the underlying governing equations of these systems by combining modern data science techniques with the rigor of traditional dynamical systems theory. For example, I investigate the computational principles of biological neurons to inform the development of neuroscience-inspired and physics-informed machine learning algorithms and neural computing methods.

  • Dynamical system theory and nonlinear dynamics
  • Mathematical neuroscience and theory of neuronal dynamics
  • Statistical physics and stochastic dynamics
  • Geometric singular perturbation theory
  • Complex systems theory and adaptive network dynamics
  • Chaos- and noise-induced resonance and synchronization phenomena
  • Self-organization and critical dynamics in  adaptive systems
  • Inference in dynamical systems
  • Data-driven methods in dynamical systems and neurodynamics
  • Bayesian methodology for high-dimensional and complex data
  • Computation through neural population dynamics
  • Statistical and computational methods in neuroscience and neural data (EEG, MEG) analysis
  • Spiking neural networks and their applications
  • Deep convolutional neural networks, recurrent neural networks, long short-term memory network
  • Physics-informed machine learning and constrained optimization
  • Neuroscience-inspired machine learning: liquid-state machines & echo-state networks
  • In particular, the interfaces between the above fields!

  • 04/2025: Co-organizer of the Conference on Women in Data Science, FAU, Erlangen, Germany
  • 04/2024: Co-organizer of the Conference on Women in Data Science, FAU, Erlangen, Germany
  • 04/2023: Co-organizer of the Conference on Women in Data Science, FAU, Erlangen, Germany
  • 03/2020 – 07/2021: Organizer of the Online Seminar Series on Dynamics and Control (93 talks), FAU
  • 11/2020: Organizer of the Mini-workshop on Neuronal Dynamics (3 talks), FAU
  • 11/2020: Organizer of the Mini-workshop on Robots Learning, Optimization & Control (4 talks), FAU
  • 10/2020: Organizer of the Mini-workshop on Hyperbolic Problems (5 talks), FAU

  • 03/2025: Invited Lecture at the FAU Research Training Group FRASCAL (fracture across scales) on machine learning, recurrent neural networks, and physics-informed neural networks
  • 03/2025: Der Tag der  Mathematik, Department Mathematik, FAU, Erlangen
  • 06/2016: Science Communicator at the  Lange Nacht der Wissenschaften 2016, Inselstrasse 22, Leipzig, Germany

  • AIP Advances
  • Applied Physics and Engineering
  • Applied Physics Letters
  • Applications of Mathematics
  • Brain Sciences
  • Chaos: An Interdisciplinary Journal of Nonlinear Science
  • Cognitive Neurodynamics
  • Communications in Nonlinear Science and Numerical Simulations
  • Discrete Dynamics in Nature and Society
  • European Physical Journal Plus
  • European Physical Journal Special Topics
  • Fluctuation and Noise Letters
  • Frontiers in Computational Neuroscience
  • Journal of Computational and Nonlinear Dynamics
  • Journal of Mathematical Biology
  • Journal of  Sound and Vibration
  • International Journal of Bifurcation and Chaos
  • Mathematics (ISSN 2227-7390)
  • Mathematical Methods in the Applied Sciences
  • Neural Processing Letters
  • Neural Networks
  • Nonlinear Dynamics: An International Journal of Nonlinear Dynamics and Chaos
  • Physica A: Statistical Mechanics and its Applications
  • Physica D: Nonlinear Phenomena
  • Physical Review E
  • Physics Letters A
  • Reviews of Modern Physics