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 (N. N.)
Autonomous Motion (Schaal)	Empirical Inference (Schölkopf)	Modern Magnetic Systems (Schütz)	New Materials and Biosystems (Spatz)

Research Groups

Soft Matter (Max Planck Fellow) (C. Bechinger)	Machine Learning and Computational Biology (K. Borgwardt)	Micro, Nano, and Molecular Systems (MPG) (P. Fischer)	Membrane Biophysics (A. Garcia-Saez)
Non-equilibrium Systems (M. Krüger) (Emmy Noether)	Smart Nanoplasmonics (N. Liu)	Biomolecular Hydrogels (R. Richter)	Semiconductor Biosensors (Zeitler/ Becker-Freyseng)
nano.AR (J.-H. Dirks)	Stuttgart Center for Electron Microscopy (StEM) (van Aken)