Marius Yamakou

Marius Yamakou is a Researcher and Lecturer at the Department of Data Science (DDS) within the Faculty of Sciences at Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU). He is also an Interim Professor in the same department (10/2024–03/2025) and a Habilitation Candidate in Applied Mathematics (2019–present).

• Education: Ph.D. in Mathematics (2014–2018), IMPRS Scholarship (2014–2018).

Dr. Yamakou's research focuses on applied mathematics, theoretical physics, and machine learning to model and control complex dynamical systems in neuroscience and physical/biological systems. His work merges dynamical systems theory, non-equilibrium statistical physics, and data-driven methods to uncover governing equations and devise optimal control strategies.

His recent publications analyze diversity-induced resonance, STDP-driven synchronization, and noise-optimized neural dynamics. Key areas include spiking neural networks, physics-informed neural networks, and self-organization in adaptive systems.

• Scientific Awards: DFG Research Grant (2021–2023, €200K), IMPRS Scholarship (2014–2018).

Dr. Yamakou supervises master’s students on topics like noise-induced resonance optimization and physics-informed neural network stability, including industry collaborations. He organizes the Conference on Women in Data Science (2023–2025) and has reviewed for 15+ journals in nonlinear dynamics and computational neuroscience.