The main research aim of our group is the development and analysis of individual-based mathematical models of collective behavior, which explicitly take the sensory perception at the individual level into account, as the proximate mechanism of social interactions in organismic systems (insects, fish, birds). Using our modeling approach, which combines state-of-art statistical physics methods, simplified models of sensory perception, and direct empirical input from our experimental partners, we aim at a systematic investigation of fundamental properties and limitations of sensory perception in the context of information transfer within animal groups. Our theoretical work focuses on modeling, mathematical analysis, and numerical simulations. However, we collaborate closely with the Couzin Lab at the Department of Collective Behavior, MPI for Ornithology / University Konstanz and the Krause Lab, Department of Fish Biology and Ecology at the IGB Berlin.

Our main research activity focuses on the following interconnected research questions:

  1. Do schools, flocks & swarms in biology – from cellular agregates to animal groups – share common functional features as collective information processing system?
  2. How does collective behavior emerge from sensory inputs? Here, we focus on question on how individuals integrate visual social information and use it to coordinate their motion.
  3. How do animal groups perform collective decisions under sensory constraints? Here, the central question is how animal groups are able to perform near-optimal and robust collective decisions despite sensory constraints and highly variable environments.

Further research interest (current & past research):

Emergence of Collective Motion and Novel States of Active Matter


Onset of collective behavior in models models with empirically motivated, phenomological interactions, which go beyond ‘minimal’ alignment models, e.g. selective attraction-repulsion or combined alignment+anti-alignment interactions; Emergence of novel states of active matter in simple self-propelled particle systems, different from the orientationally ordered fluid states (Toner and Tu), such as active turbulence, or spatially periodic structures (active smectic pattern, active crystals).

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Impact of spatio-temporal behavioral constraints on cooperation and competition

Understanding of evolutionary constraints and biological function by simple evolutionary models directly motivated by experimental observation, which include empirically observed spatio-temporal constraints.

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Coarse-grained mathematical description of active matter systems

grossmann_PRL_fig4Derivation of coarse-grained (hydrodynamic) equation of motion for macroscopic observables such as density or momentum fields from microscopic equations of motion for interacting self-propelled particle systems. Systematic analysis of the resulting hydrodynamic equations, which enable us to construct phase diagrams for the corresponding model systems.

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Modeling Individual and Collective Chemotaxis

Agent-based stochastic models of individual directed migration and collective behavior mediated by chemoattractants.

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Stochastic dynamics far from equilibriumpv_web

Modeling of physical and biological systems using stochastic differential equation, with a focus on the theory and dynamics of so-called active Brownian particles.

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