Advances in Spatial Machine Learning 2027
A Two-Day Scientific Workshop
Workshop Overview
This two-day scientific workshop aims to bring together leading researchers in the field of spatial machine learning. Unlike many conferences that focus on showcasing achievements, our goal is to address unsolved issues and open questions, fostering innovation and collaboration.
Key Topics
- Process-informed and knowledge-guided machine learning
- Geospatial foundation models, embeddings and multimodal AI
- Uncertainty quantification in spatial machine learning
- Model generalizability in non-stationary environmental regimes
- Explainable GeoAI
- Open session – we welcome participants to propose relevant topics.
Location and Date
The workshop will take place 18–19 March 2027 in Jena, Germany.
The precise venue and practical information will be announced in due course.
Program
The session topics, chairs and final timings are currently being prepared.
| Day/time | Program |
|---|---|
| Wed, Mar 17 | |
| 19:00–… | Ice-breaker (details to follow) |
| Thu, Mar 18 | |
| 9:00–10:30 | Welcome and introductions |
| 10:30–11:00 | Coffee break |
| 11:00–12:30 | Session 1 |
| 12:30–13:30 | Lunch |
| 13:30–15:00 | Session 2 |
| 15:00–15:30 | Coffee break |
| 15:30–17:00 | Session 3 |
| Evening | Joint dinner (details to follow) |
| Fri, Mar 19 | |
| 9:00–10:30 | Session 4 |
| 10:30–11:00 | Coffee break |
| 11:00–12:30 | Session 5 |
| 12:30–13:30 | Lunch |
| 13:30–15:00 | Session 6 |
| 15:00–15:30 | Coffee break |
| 15:30–17:00 | Wrap-up and future plans |
Posters
If you would like to present a poster related to your work in spatial machine learning, we will have a poster session area available during all coffee breaks and lunch sessions.
Participants
The list of invited participants will be announced in due course.
Expected Outcomes
By bringing together experts in the field, we anticipate:
- Identifying key challenges and research priorities in spatial machine learning
- Fostering collaborations between different research groups
- Developing guidelines for best practices in spatial machine learning documentation and validation
- Generating ideas for future research projects and potential funding opportunities
This workshop represents a unique opportunity to shape the future of spatial machine learning in environmental research by focusing on open questions and challenges.
Organizers
Supported by
