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
Website

Regina Ammicht Quinn

Ethics of Science
Website

Sabine Andergassen

focuses on quantum many-body theory
Website

Harald Baayen

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

Philipp Berens

develops algorithms for analysing multimodal data in neuroscience and clinical diagnostics
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Matthias Bethge

Computational Neuroscience and Machine Learning
Website

Michael Black

Computer Vision
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Martin Butz

Cognitive Science
Website

Andreas Geiger

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

Matthias Hein

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

develops algorithms for, and as, learning machines
Website

Enkelejda Kasneci

Perception Engineering
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Oliver Kohlbacher

Bioinformatics
Website

Hendrik Lensch

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

works on the theoretical foundations and limitations of machine learning
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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.
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Katja Kay Nieselt

Bioinformatics
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Mijung Park

Privacy Preserving Machine Learning 
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Nico Pfeifer

Medical Informatics
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Wolfgang Rosenstiel

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

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

Geoscience
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Fabian Sinz

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

Wolfgang Spohn

Philosophy of Science
Website

Sonja Utz

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

Probabilistic Learning 
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Felix Wichmann

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

Robotics
Website