Professorships established by the Cluster
Robert Bamler
Data Science and Machine Learning
Robert Bamler develops approximate algorithms that scale up Bayesian inference to large data sets and powerful probabilistic models. His research provides new tools for natural scientists, highly effective codecs for data compression, and the foundations for a new kind of equitable machine learning in decentralized networks.
Jakob Macke
Our goal is to accelerate scientific discovery using machine learning and artificial intelligence (AI): We develop computational methods that help scientists interpret empirical data and use them gain scientific insights.
Senior Professorship established by the Cluster
Wolfgang Spohn
Wolfgang Spohn's areas of competence are epistemiology and philosophy of science, with a special focus on logic.
Professorships supported by the Cluster
Manfred Claassen
Clinical Bioinformatics, Medical Faculty, University of Tübingen
Manfred Claassen uses machine learning for single-cell biology in health and disease.
Stephan Eckstein
Mathematical Methods in Computer Science, Department of Mathematics, University of Tübingen
Stephan Eckstein works at the intersection of probability theory and machine learning, with a particular focus on statistical distances and efficient computational methods.
Michèle Finck
Law and Artificial Intelligence, Department of Law, University of Tübingen
Michèle Finck's research focuses on law and artificial intelligence with a particular emphasis on data (protection) law and governance.
Gerard Pons-Moll
Continuous Learning of Multimodal Data Streams, Department of Computer Science, University of Tübingen
Gerard Pons-Moll's research lies at the intersection of Machine Learning, Computer Vision and Computer Graphics. His goal is to build digital humans that look and behave like real ones.
Bob Williamson
Foundations of Machine Learning Systems, Department of Computer Science, University of Tübingen
Bob Williamson is interested in understanding and designing machine learning systems as a whole. To that end, he is pursuing theoretical questions regarding machine learning problems and how they relate to each other.