Advances in Spatial Machine Learning 2026

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

Validation and Preservation of Spatial Patterns: Ensuring models provide accurate local predictions while preserving important spatial patterns.
(Spatial) xAI
How to ensure that the spatial ML model is useful?: how to avoid overfitting, do we need better algorithms or better training and validation data?
Common mistakes in spatial ML
New methods/emerging trends (e.g., foundational models, conformal predictions, etc.)
An “open” session - we welcome participants to propose relevant topics.

Location and Date

The workshop will take place 9-10 April 2026 at the University of Tartu Library, W. Struve tn 1, 50091 Tartu, Estonia.

Program

Day/time	Topic
Wed, Apr 8
19:30–…	Ice breaker at RP9
Thu, Apr 9
9:00–10:30	Introductions
10:30–11:00	Coffee break/ Posters
11:00–12:30	Session: Common mistakes/challenges in spatial ML. Chair: Alexander Brenning
12:30–13:30	Lunch/ Posters
13:30–15:00	Session: How to ensure that the spatial ML model is useful? Chair: Laura Poggio
15:00–15:30	Coffee break/ Posters
15:30–17:00	Session: Spatial validation. Chairs: Hanna Meyer, Jakub Nowosad, Mahdi Khodadadzadeh
18:00–19:30	City Excursion
19:30–…	Joint dinner at Kolm Tilli
Fri, Apr 10
9:00-10:30	Session: xAI in spatial ML. Chair: Lily-Belle Sweet
10:30-11:00	Coffee break /Posters
11:00-12:30	Emerging trends: Foundation models in spatial ML. Chair: Jonas Schmidinger
12:30-13:30	Lunch /Posters
13:30-15:00	Emerging trends: DGGS in spatial ML. Chair: Alexander Kmoch
15:00-15:30	Coffee break /Posters
15:30-17:00	Wrap-up and future plans

Open session: 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. We especially encourage PhD students to bring and present their posters.

Participants

We invited researchers actively working on spatial machine learning and deep learning:

Alexander Brenning
Laura Poggio
Felix Henkel
Jonas Schmidinger
Jonathan Frank
Lily-belle Sweet
Mahdi Khodadadzadeh
Alexander Kmoch
Iris Luik
Liina Hints
Jeonghwan Choi
Evelyn Uuemaa
Marta Jemeljanova
Hanna Meyer
Jakub Nowosad

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 ecological research by focusing on open questions and challenges.