Associate Cluster Members

The Cluster "Machine Learning" currently comprises 9 associate members, i.e. scientists that are not directly involved in the field of machine learning, but who are willing to open up new collaborations.

There is the possibility of adding new members. Information about the admission procedure is provided by the Central Office of the Cluster.

Peter Dayan

works on neural reinforcement learning, studying the computational, behavioural and neural substrates of decision-making


Todd Ehlers

research interests are in the interactions between climate, tectonics, and biota during mountain building

Gerhard Jäger

conducts research on the modeling of language diversity and language change, utilizing machine learning and Bayesian statistical inference

Augustin Kelava

is interested in psychometrics, estimation of semi- and nonparametric latent variable structural equation models, and regularization in Bayesian models



Zhaoping Li

works on vision and olfaction in the brain, and other related topics such as memory, neural circuits and networks, information theory, signal processing and inference


Detmar Meurers

work focuses on empirically rich, linguistically insightful models of human language, especially in the context of language learning and in ecologically valid, real-life education


Martin Oettel

works on problems in Statistical Physics and utilizes Machine Learning to analyze simulation data and to build density functional models

Dominik Papies

use modern econometric methods and diverse data sets to understand the impact of digitization and new technology on markets, consumers, and business models

Frank Schreiber

is interested in the physics of molecular and biological matter, studied in particular with scattering techniques