NeurIPS 2026 · Paris, France · Dec 11 / 12
2nd Workshop on Advances in Representation Learning for Earth Observation
Bringing together machine learning, computer vision, and Earth sciences to advance robust, interpretable, and scalable models for monitoring and predicting our planet.
About REO
A forum for representation learning in Earth Observation
The second edition of the Representation Learning for Earth Observation (REO) workshop brings together researchers and practitioners from machine learning, computer vision, and Earth sciences. With the growing availability of large-scale, multimodal EO data and the rise of powerful foundation models, new opportunities emerge for integrating data-driven approaches across sensing modalities and application domains.
REO provides a venue for novel technical methods, scientific applications, and system-level innovations — fostering exchange between academia and industry, and policy stakeholders.
Call for Papers
Topics of Interest
We invite contributions spanning technical methods, scientific applications, and system-level innovations across EO, environmental monitoring, and related Earth sciences.
Machine Learning for EO
Domain-adaptive models; continual and online learning; multi-modal fusion; human-in-the-loop and active learning strategies.
EO Foundation Models
Training paradigms, evaluation and interpretability, uncertainty quantification, and causal modeling for EO foundation models.
Embeddings & Compression
Encodings for efficient storage, retrieval, and search in large EO archives; semantic compression for scalable analysis.
Physics-based & Hybrid Modeling
Integration of Radiative Transfer Models and other physical simulators into ML pipelines; hybrid AI–physics parameter retrieval.
Earth Science & Ecology Applications
Geophysical parameter estimation, urban and rural mapping, weather/climate forecasting, geohazards, biodiversity, soil and vegetation.
Data, Benchmarks & Accessibility
Multimodal data handling, cross-sensor harmonization, representative datasets, bias mitigation, open benchmarks.
Research Track
Non-archival short papers of up to 4 pages presenting novel research, preliminary results, new datasets, benchmarks, or emerging ideas. Double-blind peer review. No formal proceedings.
Highlights Track
Papers published after NeurIPS 2025 at major ML/CV venues, relevant to EO and geospatial AI. Submit the published paper with a short summary (max one page) explaining its relevance. Single-blind review.
Important Dates
| Milestone | Date (AoE) |
|---|---|
| Submission deadline | Aug 29, 2026 |
| Notification | Sep 29, 2026 |
| Camera-ready | Oct 29, 2026 |
| Workshop day | Dec 11 / 12, 2026 — Paris |
In-person presentation is required.
Submissions and reviews will be handled through the CMT platform. This service is provided for free by Microsoft and they bore all expenses, including costs for Azure cloud services as well as for software development and support.
Invited Speakers
Keynotes
Five speakers representing the diversity of the EO community — spanning academia, industry, ML, and Earth sciences.
Laura Leal-Taixé
NVIDIA / U. Toronto
Senior Research Manager leading the Dynamic Vision and Learning group. Recipient of the Sofja Kovalevskaja Award, Google Faculty Award, and an ERC Starting Grant. General Chair of ECCV 2024 and ACCV 2026.
Nuno Carvalhais
Max Planck Institute for Biogeochemistry
Group Leader and ELLIS Scholar in Machine Learning for Earth and Climate Science. Works on terrestrial ecosystem dynamics, biogeochemical cycles, and climate–biosphere interactions.
Jacqueline Campbell
Asterisk Labs
Schmidt Science Fellow and co-founder at Asterisk Labs. Studies cloud properties in overlooked satellite imagery and AI tooling for accessible Earth-scale environmental data.
Konstantin Klemmer
LGND AI / UCL (incoming)
Machine learning researcher at LGND AI and incoming Assistant Professor at UCL. Works on geospatial foundation models, self-supervised learning, and location embeddings.
Konrad Schindler
ETH Zürich
Professor of Photogrammetry and Remote Sensing at ETH Zürich. Research focuses on visual AI, remote sensing, and 3D computer vision, with contributions to global-scale mapping products at the intersection of geometric CV and EO.
Program
Provisional Schedule
Keynotes, orals, two poster sessions, and a panel – 100% of talks in person.
Morning
- 09:00 – 09:15 Welcome
- 09:15 – 09:45 Keynote 1 — Laura Leal-Taixé
- 09:45 – 10:15 Keynote 2 — Nuno Carvalhais
- 10:15 – 10:45 Keynote 3 — Jacqueline Campbell
- 10:45 – 11:00 Coffee Break
- 11:00 – 11:30 Oral Presentations
- 11:30 – 12:30 Poster Session 1
- 12:30 – 13:30 Lunch Break
Afternoon
- 13:30 – 14:00 Keynote 4 — Konstantin Klemmer
- 14:00 – 14:30 Keynote 5 — Konrad Schindler
- 14:30 – 15:30 Poster Session 2
- 15:30 – 16:00 Coffee Break
- 16:00 – 17:00 Panel Discussion & Q&A
- 17:00 – 17:15 Closing Remarks
Organizers
Loïc Landrieu
ENPC (IMAGINE / LIGM), IGN–LASTIG
Nico Lang
University of Copenhagen, Pioneer Centre for AI
Benedikt Blumenstiel
IBM Research / ETH Zürich
Ruben Cartuyvels
ESA Φ-lab, Earth System Science Hub
Nikolaos Ioannis Bountos
ESA Φ-lab
Gustau Camps-Valls
Universitat de València
Xiaoxiang Zhu
TU Munich
Ioannis Papoutsis
NTU Athens, National Observatory of Athens
Program Committee Show
We are grateful to our Program Committee for their time and expertise in reviewing submissions to REO-2. Thank you.
Expert Reviewers
- · Begüm Demir (TU Berlin/BIFOLD)
- · Jocelyn Chanussot (INRIA)
- · Charlotte Pelletier (UBS Vannes)
- · Dino Ienco (INRAE)
- · Ronny Hänsch (DLR)
- · Behnood Rasti (BIFOLD/TU Berlin)
- · Gencer Sumbul (EPFL)
- · Ribana Roscher (U. Bonn)
- · Mikolaj Czerkawski (Asterisk Labs)
- · Nicolas Longépé (ESA)
- · Johannes Jakubik (IBM)
- · Franziska Gerken (NVIDIA)
- · Valerio Marsocci (ESA)
Reviewers
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Contact
For questions about the workshop, reach out to reo-workshop@example.org.