Johannes Zierenberg

About

I am a research scientist working on complex systems, data-driven modeling, and the dynamics of biological and artificial neural networks. I combine theory from statistical physics with data-driven inference to analyze time series, uncover latent states, and understand stability and regime transitions. In parallel with my academic research, I offer freelance consulting in scientific modeling, simulation, and data analysis for complex real-world systems.

My research focuses on how collective neural dynamics emerge and respond to external interventions. Rather than treating stimulation or pharmacological inputs as static perturbations, I view interventions as control signals acting on latent neural dynamics. My goal is to develop digital twins that enable state-dependent prediction of intervention effects from time series data, providing a mechanism-aware framework for controlling neural systems.