Full Member
Cluster W3 professorship "Explainable Machine Learning"
Zeynep Akata focuses on the interplay between vision and language for learning and for explaining model decisions.
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Regina Ammicht 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.
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Sabine Andergassen's scientific activities focus on quantum many-body theory.
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Harald Baayen is interested in words: their internal structure, meaning, distributional properties, and how they are processed in language comprehension and speech production.
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Cluster Speaker
Philipp Berens develops algorithms for analysing multimodal data in neuroscience and clinical diagnostics.
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Matthias Bethge examines image processing and its neural basis in the human brain using mathematical methods and psychophysical experiments.
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Michael Black's research spans Computer Vision, Machine Learning, and Graphics, with focus on computing and understanding motion in the world from video.
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Martin Butz works on neuro-cognitive modeling of human and artificial intelligence, including its development.
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Manfred Claassen uses machine learning for single-cell biology in health and disease.
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Associate Member
Peter Dayan works on neural reinforcement learning, studying the computational, behavioural and neural substrates of decision-making.
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Associate Member
Todd Ehlers research interests are in the interactions between climate, tectonics, and biota during mountain building
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Andreas Geiger works at the intersection of computer vision, machine learning and robotics.
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Head of the Cluster's Junior Research Group "Machine Learning in Climate Science"
Bedartha Goswami is interested in nonlinear time series analysis, complex network based analysis, and in particular, the role of data uncertainties in shaping our understanding of complex real-world phenomena such as synoptic-scale climatic systems.
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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.
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Associate Member
Gerhard Jäger conducts research on the modeling of language diversity and language change, utilizing machine learning and Bayesian statistical inference.
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Enkelejda Kasneci works on the application of machine learning for intelli­gent and perceptual human-computer interaction.
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Associate Member
Augustin Kelva is interested in psychometrics, estimation of semi- and nonparametric latent variable structural equation models, and regularization in Bayesian models.
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Oliver Kohlbacher focuses on research in the analysis of omics data (genomics, proteomics, metabolomics), structural bioinformatics, and computational immunomics.
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Hendrik Lensch focuses on the entire acquisition and imaging pipeline for acquiring analyzing, generating and rendering of realistic 3D models.
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Associate Member
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.
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Cluster Speaker
Ulrike von Luxburg works on the theoretical foundations and limitations of machine learning.
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Cluster W3 professorship „Machine Learning in Science“
Jakob Macke develops machine learning algorithms for scientific discovery. 

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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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Associate Member
Detmar Meurer's 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.
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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.
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Associate Member
Martin Oettel works on problems in Statistical Physics and utilizes Machine Learning to analyze simulation data and to build density functional models.
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Associate Member
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.
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Mijung Park focuses on developing practical algorithms for privacy preserving machine learning.
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Nico Pfeifer performs research at the intersection between machine learning and medicine, dealing with biased, heterogeneous multi-view data and providing explainable models.
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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 investigates the role of soils for the environment and humankind using machine learning, geostatistics and large scale field experiments.
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Associate Member
Frank Schreiber is interested in the physics of molecular and biological matter, studied in particular with scattering techniques.
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Fabian Sinz is interested in the combination of machine learning, computational neuroscience and neuronal data.
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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.
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Sonja Utz is interested in using machine learning methods to understand (the effects of) social media use.
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Isabel Valera's research focuses on developing machine learning methods that are flexible, robust, and fair.
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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 is interested in machine learning algorithms and their applications, autonomous mobile robots, sensor integration and robot vision.
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