Prof. Dr. Marius Yamakou
Department of Data Science (DDS)
My work bridges mathematical neuroscience and machine learning. Leveraging dynamical systems theory, stochastic analysis, and physics-informed machine learning, I develop data-driven models of neurons and large-scale brain activity to better understand pathological dynamics in disorders such as epilepsy and Parkinson’s disease. Drawing inspiration from neural computation, I design neuroscience-inspired machine-learning algorithms that deepen our fundamental insight into brain function while powering new algorithms, neurotechnologies, and medical applications.
Research projects
- Dynamical systems theory
- Stochastic analysis
- Statistical physics
- Mathematical and computational neuroscience
- Data-driven methods for neuronal and brain dynamics
- Mathematical and data-driven modelling of epilepsy and Parkinson’s disease
- Neuroscience-inspired machine learning (e.g., liquid-state machines)
- Physics-informed machine learning and constrained optimisation
No projects found.
2026
- Babaeian, B., & Yamakou, M. (2026). A Lyapunov stability proof and a port-Hamiltonian physics-informed neural network for chaotic synchronization in memristive neurons. Applied Mathematics and Computation, 530. https://doi.org/10.1016/j.amc.2026.130157
- Savaliya, D., & Yamakou, M. (2026). Self-induced stochastic resonance: A physics-informed machine learning approach. Chaos Solitons & Fractals, 207. https://doi.org/10.1016/j.chaos.2026.117998
2025
- Patriarca, M., Scialla, S., Heinsalu, E., Yamakou, M., & Cartwright, J.H. (2025). Dynamical equivalence between resonant translocation of a polymer chain and diversity-induced resonance. Chaos, 35(7). https://doi.org/10.1063/5.0262633
- Scialla, S., Patriarca, M., Heinsalu, E., Yamakou, M., & Cartwright, J.H. (2025). Effect of diversity distribution symmetry on global oscillations of networks of excitable units. Physical Review E, 112(5). https://doi.org/10.1103/lvb3-dc11
2024
- Kobiolka, J., Habermann, J., & Yamakou, M. (2024). Reduced-order adaptive synchronization in a chaotic neural network with parameter mismatch: a dynamical system versus machine learning approach. Nonlinear Dynamics. https://doi.org/10.1007/s11071-024-10821-6
- Metzner, C., Yamakou, M., Voelkl, D., Schilling, A., & Krauß, P. (2024). Quantifying and Maximizing the Information Flux in Recurrent Neural Networks. Neural Computation, 36(3), 351-384. https://doi.org/10.1162/neco_a_01651
- Shamsara, E., Yamakou, M., Atay, F.M., & Jost, J. (2024). Dynamics of neural fields with exponential temporal kernel. Theory in Biosciences. https://doi.org/10.1007/s12064-024-00414-7
- Yamakou, M., Zhu, J., & Martens, E.A. (2024). Inverse stochastic resonance in adaptive small-world neural networks. Chaos, 34(11). https://doi.org/10.1063/5.0225760
2023
- Yamakou, M., Desroches, M., & Rodrigues, S. (2023). Synchronization in STDP-driven memristive neural networks with time-varying topology. Journal of Biological Physics. https://doi.org/10.1007/s10867-023-09642-2
- Yamakou, M., & Inack, E.M. (2023). Coherence resonance and stochastic synchronization in a small-world neural network: an interplay in the presence of spike-timing-dependent plasticity. Nonlinear Dynamics. https://doi.org/10.1007/s11071-023-08238-8
- Yamakou, M., & Kuehn, C. (2023). Combined effects of spike-timing-dependent plasticity and homeostatic structural plasticity on coherence resonance. Physical Review E, 107(4). https://doi.org/10.1103/PhysRevE.107.044302
- Zhu, J., & Yamakou, M. (2023). Self-induced-stochastic-resonance breathing chimeras. Physical Review E, 108(2). https://doi.org/10.1103/PhysRevE.108.L022204
2022
- Yamakou, M., Heinsalu, E., Patriarca, M., & Scialla, S. (2022). Diversity-induced decoherence. Physical Review E, 106(3). https://doi.org/10.1103/PhysRevE.106.L032401
- Yamakou, M., Tran, T.D., & Jost, J. (2022). Optimal Resonances in Multiplex Neural Networks Driven by an STDP Learning Rule. Frontiers in Physics, 10. https://doi.org/10.3389/fphy.2022.909365
2021
- Bönsel, F., Krauß, P., Metzner, C., & Yamakou, M. (2021). Control of noise-induced coherent oscillations in three-neuron motifs. Cognitive Neurodynamics, 16, 941-960. https://doi.org/10.1007/s11571-021-09770-2
- Yamakou, M., & Tran, T.D. (2021). Lévy noise-induced self-induced stochastic resonance in a memristive neuron. Nonlinear Dynamics. https://doi.org/10.1007/s11071-021-07088-6
2020
- Yamakou, M. (2020). Chaotic synchronization of memristive neurons: Lyapunov function versus Hamilton function. Nonlinear Dynamics. https://doi.org/10.1007/s11071-020-05715-2