General interest
I'm interested in the general information theoretic principles from which adequate task performance emerges. I believe to understand this, one has to both examine 'biological implementations' of learning system and to investigate the performance of hypothesized principles in 'machine learning'. To be involved with both perspectives, in my projects I employ machine learning techniques to analyze neural data.

Projects
Olfactory coding in the mouse olfactory bulb. In collaboration with J. Schumacher and H. Spors, MPI for Biophysics, Frankfurt, funded by DFG Priority Programme SPP1392: "Integrative Analysis of Olfaction"

Olfactory coding in the drosophila lateral horn. In collaboration with A. Strutz and S.Sachse, MPI for Chemical Ecology, Jena

Selected Publications
Ulrich Rührmair, Frank Sehnke, Jan Sölter, Gideon Dror, Srinivas Devadas, and Jürgen Schmidhuber. 2010. Modeling attacks on physical unclonable functions. In Proceedings of the 17th ACM conference on Computer and communications security (CCS '10) DOI=10.1145/1866307.1866335

Periklis Papadopoulos, Jan Sölter, Friedrich Kremer. 2009. Hierarchies in the structural organization of spider silk - a quantitative model. In Colloid & Polymer Science