Tilo Schwalger

Tilo Schwalger is an Assistant Professor in Computational Neuroscience and Data Assimilation at the Institut für Mathematik, Technische Universität Berlin. He leads a junior research group affiliated with the Bernstein Network Computational Neuroscience (BCCN) and the Einstein Center Digital Future (ECDF). His work bridges experimental neuroscience with theoretical models, focusing on multiscale modeling of brain activity.

• PhD in Theoretical Physics (2013, Max Planck Institute Dresden & Humboldt-Universität Berlin)
• Diploma in Physics (2006, Humboldt-Universität Berlin)
• DAAD-funded studies at Lomonosov Moscow State University (2003-2004)

His research spans the mathematical modeling of neural activity across scales, from microscopic spiking neurons to mesoscopic neuronal populations and macroscopic brain dynamics. Using tools from statistical physics, stochastic processes, and nonlinear dynamics, he develops frameworks like mean-field theories, coarse-graining techniques, and stochastic delay differential equations to analyze neural variability, synchronization, and information processing. Key applications include understanding cortical circuits, hippocampal replay, and associative memory mechanisms.

Recent publications highlight his focus on multiscale modeling, including finite-size networks, stochastic neural dynamics, and short-term synaptic plasticity effects. His work enables rapid simulations of large-scale brain activity through low-dimensional firing-rate models consistent with microscopic spiking neuron dynamics.

He has held postdoctoral positions at the University of Pittsburgh, Columbia University, and the École Polytechnique Fédérale de Lausanne (EPFL), and actively collaborates with experimental and theoretical labs globally.