ELLIS Programs launched

San Sebastián, Spain – The members of the European Laboratory for Learning & Intelligent Systems (ELLIS) have launched a set of ELLIS Programs at a meeting in San Sebastián in Spain. ELLIS Programs are cross-national research projects, with each being directed by two to three outstanding machine learning (ML) scientists. Each team focuses on an area that has the potential to move the needle in modern AI, thus allowing Europe to shape the technological and social AI revolution.

As a result of an international review process led by Yoshua Bengio, Professor at the University of Montreal, with the help of the CIFAR Learning in Machines and Brains Program, 11 ELLIS Programs were selected. The Ministry of Science, Research and the Arts of the State of Baden-Württemberg in Germany is funding them with one million Euros. "Baden-Württemberg sees the need for a strong European AI. We therefore support ELLIS and its programs and wish them a huge success," said Baden-Württemberg’s Science Minister Theresia Bauer.

Using the funding, each ELLIS Program can hold one workshop in 2019 and two workshops in 2020. Cyber Valley will be co-organizer of the workshops, many of which will take place in Baden-Württemberg, at the Oberwolfach Research Institute for Mathematics as well as during an upcoming Machine Learning Summer School in Tübingen.

Each ELLIS Program comprises around 10 to 15 outstanding researchers who have all made a name for themselves at one of the leading ML research institutions in Europe, among them ETH Zürich, Cambridge, Oxford, the Universities of Amsterdam and Tübingen, the French research institute for digital sciences (INRIA), and several Max Planck Institutes.

Programs and directors

Geometric Deep Learning 

• Max Welling (University of Amsterdam / Qualcomm, NL)
• Michael Bronstein (Imperial College, UK / USI Lugano, CH)
• Taco Cohen (University of Amsterdam / Qualcomm, NL)

Robust Machine Learning

• Yee Whye Teh (University of Oxford, DeepMind)
• Chris Holmes (University of Oxford, Alan Turing Institute)
• Sami Kaski (Finnish Centre of Excellence in Computational Inference Research at Aalto University)

Interactive Learning and Interventional Representations

• Nicolò Cesa-Bianchi (University of Milano)
• Andreas Krause (ETH Zurich)
• Bernhard Schölkopf (Max Planck Institute for Intelligent Systems, Tübingen)

Machine Learning and Computer Vision

• Cordelia Schmid (INRIA, Grenoble)
• Yair Weiss (Hebrew University, Jerusalem)
• Bernt Schiele (Max Planck Institute for Informatics, Saarbrücken)

ELLIS Robot Learning: Closing the Reality Gap!

• Jan Peters (TU Darmstadt & Max Planck Institute for Intelligent Systems Tübingen)
• Tamim Asfour (Karlsruhe Institute of Technology KIT)
• Aude Billard (Ecole polytechnique fédérale de Lausanne)

Human-centric Machine Learning

• Nuria Oliver (Data-Pop Alliance and Royal Academy of Engineering, Spain)
• Plamen Angelov (Lancaster University)
• Adrian Weller (University of Cambridge/Alan Turing Institute)

Theory, Algorithms and Computations of Modern Learning Systems

• Francis Bach (Ecole Normale Supérieure and INRIA, Paris)
• Philipp Hennig (University of Tübingen & Max Planck Institute for Intelligent Systems)
• Lorenzo Rosasco (University of Genoa, IIT & MIT)

Quantum and physics based machine learning

• Riccardo Zecchina (Bocconi University, Milan)
• Bert Kappen (Radboud University, Netherlands)

Natural Intelligence

• Matthias Bethge (University of Tübingen)
• Y-Lan Boureau (Facebook AI Research, New York)
• Peter Dayan (Max Planck Institute for Biological Cybernetics, Tübingen)

ELLIS Health

• Gunnar Rätsch (ETH Zurich)
• Mihaela van der Schaar (University of Cambridge)
• Oliver Stegle (DKFZ/EMBL Heidelberg)

Machine Learning for Earth and Climate Sciences

• Gustau Camps-Valls (Universitat de València)
• Markus Reichstein (Max Planck Institute for Biogeochemistry, Jena)