Cluster Full Members

The Cluster "Machine Learning" currently comprises 28 full members, i.e. scientists working directly in the field of machine learning.

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

Zeynep Akata

focuses on the interplay between vision and language for learning and for explaining model decisions

Regina Ammicht Quinn

works on questions of ethics, especially questions of cultural ethics, ethics and security, technology ethics, ethical questions of digital technology development and ethical questions of gender discourse

Sabine Andergassen

focuses on quantum many-body theory

Harald Baayen

is interested in words: their internal structure, meaning, distributional properties, and how they are processed in language comprehension and speech production

Philipp Berens

develops algorithms for analysing multimodal data in neuroscience and clinical diagnostics


Matthias Bethge

examines image processing and its neural basis in the human brain using mathematical methods and psychophysical experiments

Michael Black

is interested in machine vision (optical flow estimation, 3D shape models, human shape and motion analysis, robust statistical methods, probabilistic models of the visual world) and computational neuroscience (probabilistic models of the neural code and applications of neural decoding in neural prosthetics)


Martin Butz

works on neuro-cognitive modeling of human and artificial intelligence, including its development

Andreas Geiger

works at the intersection of computer vision, machine learning and robotics

Matthias Hein

works on theoretical guarantees for machine learning algorithms with the goal of robust, safe and explainable learning

Philipp Hennig

develops algorithms for, and as, learning machines

Enkelejda Kasneci

is mainly interested in human vision, eye-tracking technology and applications, and driver assistance systems

Oliver Kohlbacher

focuses on research in the analysis of omics data (genomics, proteomics, metabolomics), structural bioinformatics, and computational immunomics

Hendrik Lensch

focuses on the entire acquisition and imaging pipeline for acquiring analyzing, generating and rendering of realistic 3D models  

Ulrike von Luxburg

works on the theoretical foundations and limitations of machine learning


Georg Martius

works on ML algorithms for embodied agent to make them learn in a develop­mental fashion. Under the hood we study theory and practice of reinforcement learning algorithms, repre­sentation learning, and non-standard deep-learning architectures.

Katja Kay Nieselt

focuses on expression analysis and RNA bioinformatics; her her group has designed algorithms and software systems for the analysis of microarray and RNAseq data

Mijung Park

focuses on developing practical algorithms for privacy preserving machine learning

Nico Pfeifer

performs research at the intersection between machine learning and medicine, dealing with biased, heterogeneous multi-view data and providing explainable models

Wolfgang Rosenstiel

is working on applications of machine learning in safety critical systems ranging from automotive embedded systems to brain computer interfaces

Bernhard Schölkopf

is largely dedicated to machine learning and causal inference, important bran­ches in the broad research field of artificial intelligence

Thomas Scholten

investigates the role of soils for the environment and humankind using machine learning, geostatistics and large scale field experiments

Fabian Sinz

is interested in the combination of machine learning, computational neuroscience and neuronal data

Wolfgang Spohn

is interested in formal epistemology, philosophy of science, and the theory of rationality and focuses in particular on causal inference and the representation of uncertainty

Sonja Utz

is interested in using machine learning methods to understand (the effects of) social media use

Isabel Valera

focuses on developing machine learning methods that are flexible, robust, and fair

Felix Wichmann

investigates human visual perception and cognition combining psychophysical experiments with computational modelling and machine learning

Andreas Zell

is interested in machine learning algorithms and their applications, autonomous mobile robots, sensor integration and robot vision