Cluster Members
The Cluster "Machine Learning" currently comprises 51 Members.
There is the possibility of adding new members.
Information about the admission procedure is provided by the Central Office of the Cluster.
A
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.
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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.
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Sabine Andergassen
Full Member
Sabine Andergassen's scientific activities focus on quantum many-body theory.
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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.
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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.
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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
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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.
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Philipp Berens
Full Member / Cluster Speaker
Philipp Berens develops algorithms for analysing multimodal data in neuroscience and clinical diagnostics.
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Matthias Bethge
Full Member
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
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.
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Martin Butz
Full Member
Martin Butz works on neuro-cognitive modeling of human and artificial intelligence, including its development.
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Manfred Claassen
Full Member
Manfred Claassen uses machine learning for single-cell biology in health and disease.
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D
Peter Dayan
Associate Member
Peter Dayan works on neural reinforcement learning, studying the computational, behavioural and neural substrates of decision-making.
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E
Todd Ehlers
Associate Member
Todd Ehlers research interests are in the interactions between climate, tectonics, and biota during mountain building
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G
Sergios Gatidis
Associate Member
Sergios Gatidis works on translating machine learning methods for application in medical imaging.
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Andreas Geiger
Full Member
Andreas Geiger works at the intersection of computer vision, machine learning and robotics.
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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.
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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.
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H
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.
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Matthias Hein
Full Member
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
Full Member
Philipp Hennig develops algorithms for, and as, learning machines.
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J
Gerhard Jäger
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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K
Enkelejda Kasneci
Full Member
Enkelejda Kasneci works on the application of machine learning for intelligent and perceptual human-computer interaction.
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Augustin Kelava
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
Full Member
Oliver Kohlbacher focuses on research in the analysis of omics data (genomics, proteomics, metabolomics), structural bioinformatics, and computational immunomics.
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L
Hendrik Lensch
Full Member
Hendrik Lensch focuses on the entire acquisition and imaging pipeline for acquiring analyzing, generating and rendering of realistic 3D models.
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Igor Lesanovsky
Associate Member
Igor Lesanovsky's research focusses 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.
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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.
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Nicole Ludwig
Full Member / Leader of the Early Career 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.
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Ulrike von Luxburg
Full Member / Cluster Speaker
Ulrike von Luxburg works on the theoretical foundations and limitations of machine learning.
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M
Jakob Macke
Full Member / Cluster W3 professorship „Machine Learning in Science“
Jakob Macke develops machine learning algorithms for scientific discovery.
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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.
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Detmar Meurers
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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Katja Kay Nieselt
Full Member
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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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.
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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.
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Mijung Park
Full Member
Mijung Park focuses on developing practical algorithms for privacy preserving machine learning.
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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.
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R
Wolfgang Rosenstiel
Obituary for Prof. Dr. rer. nat. Wolfgang Rosenstiel
On August 19, 2020 in Tübingen, Prof. Dr. Wolfgang Rosenstiel passed away after a long battle with illness.
S
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.
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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.
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Frank Schreiber
Associate Member
Frank Schreiber is interested in the physics of molecular and biological matter, studied in particular with scattering techniques.
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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.
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Fabian Sinz
Full Member
Fabian Sinz is interested in the combination of machine learning, computational neuroscience and neuronal data.
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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.
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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.
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Sonja Utz
Full Member
Sonja Utz is interested in using machine learning methods to understand (the effects of) social media use.
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Isabel Valera
Full Member
Isabel Valera's research focuses on developing machine learning methods that are flexible, robust, and fair.
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Felix Wichmann
Full Member
Felix Wichmann investigates human visual perception and cognition combining psychophysical experiments with computational modelling and machine learning.
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Robert C. Williamson
starting March 2021
Full Member / W3 professorship "Foundations of Machine Learning"
Bob Williamson is to develop new scientific understanding of how socio-technical systems that include machine learning technologies can be understood, analysed, improved and managed.
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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.
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Andreas Zell
Full Member
Andreas Zell is interested in machine learning algorithms and their applications, autonomous mobile robots, sensor integration and robot vision.
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