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.
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 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
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
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
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
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 investigates how machine vision systems can learn a robust and generalizable representation of their environment similar to humans.
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.
Carsten Eickhoff studies automatic text understanding, generation, and their role in health decision making.
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
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
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
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 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 focuses on research in the analysis of omics data (genomics, proteomics, metabolomics), structural bioinformatics, and computational immunomics.
Oliver Kohlbacher's Website
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
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
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 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' 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 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 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
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 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 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 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
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 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
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
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
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