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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Regina Ammicht Quinn

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


Harald Baayen

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

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

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

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

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

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

Matthias Bethge

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

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

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

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

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

Martin Butz

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


Manfred Claassen

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


Peter Dayan

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

Reinhard Drews

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


Stephan Eckstein

Stephan Eckstein works at the intersection of probability theory and machine learning, with a particular focus on statistical distances and efficient computational methods.
Stephan Eckstein's Website

Katharina Eggensperger

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.

Carsten Eickhoff

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


Michèle Finck

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

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

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


Andreas Geiger

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

Konstantin Genin

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

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

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

Anna Gumpert

Anna Gumpert studies the effects of digitalization on firms and their employees, with an emphasis on understanding the economic mechanisms driving the impact of new digital technologies.
Anna Gumpert's Website


Moritz Hardt

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

Tobias Hauser

Tobias investigates the neural and computational mechanisms that underlie mental illnesses, such as obsessive-compulsive disorder. In his work, he combines neuroimaging, pharmacology, and computational modelling in youths and adults with and without mental health problems.
Tobias Hauser's Website

Matthias Hein

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

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


Gerhard Jäger

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


Tobias Kaufmann

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

Charles Mberi Kimpolo

Charles leads the implementation of Work Integrated Learning and Innovation programs at AIMS to develop new industry needs-driven capacity development programs and support AIMS graduates in their transition to employment, entrepreneurship, and further study.
Charles Mberi Kimpolos Website

Augustin Kelava

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

Michael Knaus

Michael Knaus is interested in machine learning assisted causal effect estimation and its applications in empirical economics.

Michael Knaus' Website

Oliver Kohlbacher

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

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

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

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

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

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

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

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


Jakob Macke

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

Georg Martius

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

Celestine Mendler-Dünner

Celestine Mendler-Dünner focuses on machine learning in social context and the role of prediction in digital economies.
Celestine Mendler-Dünner's Website

Detmar Meurers

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

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


Martin Oettel

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

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

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

Gerard Pons-Moll

Gerard Pons-Moll's goal is to train machines to perceive and represent the 3D world form visual observations, and build digital humans that look and behave like real ones.
Gerard Pons-Moll's Website


Kira Rehfeld

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

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

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

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

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

Wolfgang Spohn

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

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

Thomas Thiemeyer

Thomas Thiemeyer deals with the social relevance of artificial intelligence and has dealt in particular with the Tübingen discussion about Cyber Valley as part of the exhibition Cyber and the City (11.2.2023-21.1.2024 in the Stadtmuseum Tübingen)

Thomas Thiemeyers Website

Daniela Thorwarth

Daniela Thorwarth uses machine learning to automatize processes and analyze imaging and treatment data in cancer radiotherapy.
Daniela Thorwarth's Website


Sonja Utz

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


Claire Vernade

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

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

Robert C. Williamson

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

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

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

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

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