Programs
In addition to ELLIS sites, a European network of top researchers working at locations throughout Europe is being established, organized into ELLIS Programs. These Programs, directed by outstanding European researchers and including leading researchers as Program Fellows, focus on high-impact problem areas that have the potential to move the needle in modern AI.
The ELLIS Programs are inspired by the CIFAR Program model, and closely collaborate with the CIFAR LMB (Learning in Machines and Brains) Program. Each Program has a budget for 2-3 workshops/year to enable meetings of 10-15 Fellows plus guests for intensive scientific exchange. Workshops can be co-located with academic meetings (usually) held in Europe, or organised as stand-alone events, usually at (and with the support of) ELLIS unit sites.
Program directors can invite guests to individual workshops. This ensures that fresh outside ideas are represented, and also that a wider community benefits from the workshops. Fellow Programs are started by a peer review process. The next deadline for submitting a proposal will be announced in 2023. Instructions on how to submit a program proposal can be found here.
While the first batch of Programs was reviewed by CIFAR LMB, subsequent applications are being reviewed by existing ELLIS fellows. For submissions and questions please send an email to research.programs.area@ellis.eu.
ELLIS Programs
- ELLIS Health
- ELLIS Robot Learning: Closing the Reality Gap!
- Geometric Deep Learning
- Human-centric Machine Learning
- Interactive Learning and Interventional Representations
- Learning for Graphics and Vision
- Machine Learning and Computer Vision
- Machine Learning for Earth and Climate Sciences
- Machine Learning for Molecule Discovery
- Multimodal Learning Systems
- Natural Intelligence
- Natural Language Processing
- Quantum and Physics Based Machine Learning
- Robust Machine Learning
- Semantic, Symbolic and Interpretable Machine Learning
- Theory, Algorithms and Computations of Modern Learning Systems
Latest News
28 January 2025
Exploring Overparametrization, Regularization, and Uncertainty in Machine Learning: Insights from the Oberwolfach Workshop
The Oberwolfach workshop, jointly organized by the ELLIS Program for Theory, Algorithms, and Computations and the Program for I...
28 January 2025
Start of New AI for Good Webinar Series: "From Molecules to Models" Featuring ELLIS Programs
This series aims to highlight the contributions of ELLIS Programs to AI in life sciences and foster interdisciplinary collabora...
08 August 2024
“Machine learning methods have the potential to drastically reduce the time and cost involved in molecular discovery.”
The discovery of new molecules with desired functions holds immense potential for addressing global challenges such as pandemic...
