Our goal is to understand the principles of perception,
action and learning in autonomous systems that successfully
interact with complex environments and to use this
understanding to design future systems.

The Institute studies these principles in biological,
computational, hybrid, and material systems ranging
from nano to macro scales.

We take a highly interdisciplinary approach that combines
mathematics, computation, material science, and biology.

Departments

Perceiving Systems (Black)	Theory of Inhomo- geneous Condensed Matter (Dietrich)	Phase Transformations, Thermodynamics and Kinetics (Mittemeijer)	Low-Dimensional and Metastable Materials (Rühle)
Autonomous Motion (Schaal)	Empirical Inference (Schölkopf)	Modern Magnetic Systems (Schütz)	New Materials and Biosystems (Spatz)

Research Groups

Soft Matter (Max Planck Fellow Group) (Bechinger)	Machine Learning and Computational Biology (Borgwardt)	Micro, nano, and molecular systems (MPG)(P. Fischer)	Membrane Biophysics (Garcia-Saez)
Model systems of glycan-rich cellular coats (R. Richter)	Nonlinear Spectros- copy of Bio-Inter- faces (MPG) (Roke)	Machine Learning Theory (von Luxburg)	Stuttgart Center for Electron Microscopy (StEM) (van Aken)