Cluster Members

The Cluster "Machine Learning" currently comprises 69 Members.

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

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Zeynep Akata

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.
Zeynep Akata's Website

Regina Ammicht Quinn

Full Member
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.
Regina Ammicht Quinn's Website

Sabine Andergassen

Full Member
Sabine Andergassen's scientific activities focus on quantum many-body theory.
Sabine Andergassen's Website



Harald Baayen

Full Member
Harald Baayen is interested in words: their internal structure, meaning, distributional properties, and how they are processed in language comprehension and speech production.
Harald Baayen's Website

Robert Bamler

Full Member / Cluster W2 professorship 'Data Science and Machine Learning'
Robert Bamler develops approximate algorithms that scale up Bayesian inference to large data sets and powerful probabilistic models.
Robert Bamler's Website

Christoph Bareither

Associate Member
Christoph Bareither works in the field of digital anthropology. He is interested in „cultures of artificial intelligence“ and the transformation of human-technology-relationships in the context of machine learning.
Christoph Bareither's Website

Franz Baumdicker

Full Member / Head of the Independent Research Group "Mathematical and Computational Population Genetics"
Franz Baumdicker's research focuses on mathematical models for the evolution of microbes. His group investigates how machine learning can leverage phylogenetic information in population genetics
Franz Baumdicker's Website

Christian Baumgartner

Full Member / Head of the Independent Research Group "Machine Learning in Medical Image Analysis"
Christian Baumgartner's research is at the interface of machine learning and automated medical image analysis with the goal to create safe and robust clinical prediction systems.
Christian Baumgartner's Website

Philipp Berens

Full Member / Cluster Speaker
Philipp Berens develops algorithms for analysing multimodal data in neuroscience and clinical diagnostics.
Philipp Berens' Website

Matthias Bethge

Full Member
Matthias Bethge examines image processing and its neural basis in the human brain using mathematical methods and psychophysical experiments.
Matthias Bethge's Website

Martin Biewen

Associate Member
Martin Biewen uses statistical and econometric methods to study empirical problems in labor economics, education economics and social policy.
Martin Biewen's Website

Michael Black

Full Member
Michael Black's research spans Computer Vision, Machine Learning, and Graphics, with focus on computing and understanding motion in the world from video.
Michael Black's Website

Holger Brandt

Associated Member
Holger Brandt develops statistical methods at the intersection of psychometrics and machine learning that focus on intensive longitudinal data and the identification of causal process variables.
Holger Brandt's Website

Wieland Brendel

Full Member
Wieland Brendel investigates how machine vision systems can learn a robust and generalizable representation of their environment similar to humans.

Martin Butz

Full Member
Martin Butz works on neuro-cognitive modeling of human and artificial intelligence, including its development.
Martin Butz' Website


Manfred Claassen

Full Member
Manfred Claassen uses machine learning for single-cell biology in health and disease.
Manfred Claassen's Website


Peter Dayan

Associate Member
Peter Dayan works on neural reinforcement learning, studying the computational, behavioural and neural substrates of decision-making.
Peter Dayan's Website

Reinhard Drews

Full member
The Geophyscis  group focus on near-surface geophysical imaging tackeling climate relevant research questions  on ice sheets and in terrestrial settings. Specifically we use airborne and ground-based georadar, satellite- and ground-based radar interferometry, GNSS, and numerical modeling & data integration.
Reinhard Drews' Website


Katharina Eggensperger

Full Member / Head of the Early Career Research Group "Automated machine learning for science"
Katharina Eggensperger researches how to make machine learning easily accessible and more efficient through automated machine learning (AutoML) to advance and augment scientific research.

Todd Ehlers

Associate Member
Todd Ehlers research interests are in the interactions between climate, tectonics, and biota during mountain building
Todd Ehlers' Website

Carsten Eickhoff

Full Member
Carsten Eickhoff studies automatic text understanding, generation, and their role in health decision making.
Carsten Eickhoff's Website


Michèle Finck

Full Member
Michèle Finck's research focuses on law and artificial intelligence with a particular emphasis on data (protection) law and governance.
Michèle Finck's Website

Michael Franke

Associated Member
Michael Franke uses data-driven modeling to investigate the human ability to generate and interpret language flexibly in different context.
Michael Franke's Website

Volker Franz

Associate Member
Volker Franz is interested in how humans process visual information to guide motor actions or to perform cognitive tasks. He also works on methodological and statistical topics and is interested in applications of statistical methods and ML to find better answers to these scientific questions.
Volker Franz' Website


Sergios Gatidis

Associate Member
Sergios Gatidis works on translating machine learning methods for application in medical imaging.
Sergios Gatidis' Website

Andreas Geiger

Full Member
Andreas Geiger works at the intersection of computer vision, machine learning and robotics.
Andreas Geiger's Website

Konstantin Genin

Full Member / Head of the Independent Research Group  "Epistemology and Ethics of Machine Learning"
Konstantin Genin is interested in learning-theoretic approaches to issues in the ethics and methodology of statistics and machine learning.
Konstantin Genin's Website

Martin Giese

Associate Member
Martin Giese investigates neural modeling of high-level vision and motor control, machine learning methods for representation and animation of facial and body movements, biomedical applications in neurology and psychiatry.
Martin Giese's Website

Bedartha Goswami

Full Member / Head of the Independent 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.
Bedartha Goswami's Website


Thilo Hagendorff

Associate Member
As a member of the Cluster's Ethics & Philosophy Lab, Thilo Hagendorff does research in the field of technology ethics as well as the ethics of machine learning.
Thilo Hagendorff's Website

Moritz Hardt

Full Member
Moritz Hardt's research is on the scientific foundations of machine learning and algorithmic decision making whith a focus on social questions.
Moritz Hardt's Website

Matthias Hein

Full Member
Matthias Hein works on theoretical guarantees for machine learning algorithms with the goal of robust, safe and explainable learning.
Matthias Hein's Website

Philipp Hennig

Full Member
Philipp Hennig develops algorithms for, and as, learning machines.
Philipp Hennig's Website


Gerhard Jäger

Associate Member
Gerhard Jäger conducts research on the modeling of language diversity and language change, utilizing machine learning and Bayesian statistical inference.
Gerhard Jäger's Website


Enkelejda Kasneci

Full Member
Enkelejda Kasneci works on the application of machine learning for intelli­gent and perceptual human-computer interaction.
Enkelejda Kasneci's Website​​​​​​​

Tobias Kaufmann

Associate Member
Tobias Kaufmann applies computational tools to large-scale neuroimaging and genetics data, aiming to increase our understanding of the pathophysiology underlying psychiatric disorders.
Tobias Kaufmann's Website

Augustin Kelava

Associate Member
Augustin Kelava is interested in psychometrics, estimation of semi- and nonparametric latent variable structural equation models, and regularization in Bayesian models.
Augustin Kelava's Website

Oliver Kohlbacher

Full Member
Oliver Kohlbacher focuses on research in the analysis of omics data (genomics, proteomics, metabolomics), structural bioinformatics, and computational immunomics.
Oliver Kohlbacher's Website

Thomas Küstner

Full member
Thomas Küstner is working on AI-enabled multi-parametric and multi-modality medical imaging methods in acquisition and reconstruction, and the automated analysis of clinical and epidemiological studies. His work is particularly focused on MR-based motion imaging, correction and reconstruction, and the usage of AI in MR-imaging.
Thomas Küstner's Website


Hendrik Lensch

Full Member
Hendrik Lensch focuses on the entire acquisition and imaging pipeline for acquiring analyzing, generating and rendering of realistic 3D models.
Hendrik Lensch's Website

Igor Lesanovsky

Associate Member
Igor Lesanovsky's research focuses on the theoretical physics of open and closed quantum many-body systems. He is interested in the investigation of collective phenomena, that occur e.g. near phase transitions.
Igor Lesanovsky's Website​​​​​​​

Anna Levina

Associate Member
Anna Levina aims to uncover principles of neuronal self-organization in the brain using mathematical methods and physical models.
Anna Levina's Website

Zhaoping Li

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.
Zhaoping Li's Website

Nicole Ludwig

Full Member / Head of the Independent Research Group "ML in Sustainable Energy Systems"
Nicole Ludwig is interested in developing machine learning algorithms that help build a sustainable energy system of the future.
Nicole Ludwig's Website​​​​​​​

Ulrike von Luxburg

Full Member / Cluster Speaker
Ulrike von Luxburg works on the theoretical foundations and limitations of machine learning.
Ulrike von Luxburg's Website


Jakob Macke

Full Member / Cluster W3 professorship „Machine Learning in Science“
Jakob Macke develops machine learning algorithms for scientific discovery. 
Jakob Macke's Website

Setareh Maghsudi

Full Member
Setareh Maghsudi's research focuses on developing decision-making strategies under uncertainty, conflict, and communications constraints, with future-looking applications such as the Internet of Things.
Setareh Maghsudi's Website

Georg Martius

Full Member
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.
Georg Martius' Website

Detmar Meurers

Associate Member
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.
Detmar Meurers' Website


Kay Nieselt

Full Member
Kay Nieselt focuses on expression analysis and RNA bioinformatics; her group has designed algorithms and software systems for the analysis of microarray and RNAseq data.
Kay Nieselt's Website


Peter Ochs

Full Member
Peter Ochs is interested in the development and analysis of efficient algorithms for non-smooth optimization problems, which are motivated by applications in image processing, computer vision, machine learning and statistics.
Peter Ochs' Website

Martin Oettel

Associate Member
Martin Oettel works on problems in statistical physics and utilizes machine learning to analyze simulation data and to build density functional models.
Martin Oettel's Website


Dominik Papies

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.
Dominik Papies' Website

Nico Pfeifer

Full Member
Nico Pfeifer performs research at the intersection between machine learning and medicine, dealing with biased, heterogeneous multi-view data and providing explainable models.
Nico Pfeifer's Website


Kira Rehfeld

Full Member
Kira Rehfeld investigates Earth system stability and dynamics across time and space scales, with the goal of improving climate models and enabling sustainable development.
Kira Rehfeld's Website


Samira Samadi

Full Member
Samira Samadi studies the human aspects of machine learning and uses her findings to design AI systems that efficiently and ethically augment humans' abilities rather than replacing them.
Samira Samadi's Website

Bernhard Schölkopf

Full Member
Bernhard Schölkopf is largely dedicated to machine learning and causal inference, important bran­ches in the broad research field of artificial intelligence.
Bernhard Schölkopf's Website

Thomas Scholten

Full Member
Thomas Scholten investigates the role of soils for the environment and humankind using machine learning, geostatistics and large scale field experiments.
Thomas Scholten's Website

Frank Schreiber

Associate Member
Frank Schreiber is interested in the physics of molecular and biological matter, studied in particular with scattering techniques.
Frank Schreiber's Website

Eric Schulz

Associate Member
Eric Schulz works on computational models of human intelligence, combining cognitive science, computational neuroscience, and machine learning in the attempt to build models that learn and explore like people.
Eric Schulz' Website

Wolfgang Spohn

Full Member
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.
Wolfgang Spohn's Website


Álvaro Tejero-Cantero

Full Member / Cluster core facility "Machine Learning ⇌ Science Colaboratory"
Álvaro Tejero-Cantero leads the ml ⇌ science colab. He focuses on reproducible machine learning for the sciences and the humanities. He is interested in inference of mechanistic models and explorable explanations of machine learning algorithms.
Álvaro Tejero-Cantero's Website


Sonja Utz

Full Member
Sonja Utz is interested in using machine learning methods to understand (the effects of) social media use.
Sonja Utz' Website


Isabel Valera

Full Member
Isabel Valera's research focuses on developing machine learning methods that are flexible, robust, and fair.
Isabel Valera's Website

Claire Vernade

Full member / Head of the Independent Research Group "Lifelong Reinforcement Learning"
Claire Vernade studies interactive machine learning problems where feedback loops and long-term impact of actions must be taken into account to train agents.
Claire Vernade's Website


Felix Wichmann

Full Member
Felix Wichmann investigates human visual perception and cognition combining psychophysical experiments with computational modelling and machine learning.
Felix Wichmann's Website

Robert C. Williamson

Full Member  /  W3 professorship "Foundations of Machine Learning"
Bob Williamson's goal is to develop new scientific understanding of how socio-technical systems that include machine learning technologies can be understood, analysed, improved and managed.
Bob Williamson's Website​​​​​​​

Thomas Wolfers

Associate Member
Thomas Wolfers aims to support individuals with complex health challenges by developing approaches that zoom in on the individual instead of the disorder or disease as a category. More concretely, we discover hidden factors contributing to mental health through developing and applying ML methods to high dimensional and multimodal datasets.
Thomas Wolfers' Website

Charley Wu

Full Member / Head of the Independent Research Group  "Human and Machine Cognition"
Charley Wu’s research studies the specific shortcuts and cognitive algorithms that people use to make inference tractable. His work seeks to narrow the gap between human and machine learning.  
Charley Wu's Website


Christiane Zarfl

Associate Member
Christiane Zarfl combines field and laboratory work with mathematical modelling to investigate the impact of humans on freshwater ecosystems and to better understand underlying processes and relationships - a basis for sustainable river management.
Christiane Zarfl's Website

Andreas Zell

Full Member
Andreas Zell is interested in machine learning algorithms and their applications, autonomous mobile robots, sensor integration and robot vision.
Andreas Zell's Website