Format of Workshop: Half day

GIScience 2025 Workshop on Geospatial Data Representation Learning

Representation learning has revolutionized machine learning by enabling models to extract meaningful features from raw data automatically. This workshop explores its potential in GIScience, focusing on geospatial data’s unique challenges and opportunities. We invite contributions on topics including but not limited to:

• Spatial and spatiotemporal representation learning methods.
• Applications of representation learning in urban analytics, environmental science, and mobility studies.
• Multimodal representation learning for integrating heterogeneous geospatial data.
• Theoretical advancements and model interpretability in geospatial contexts.

We welcome research papers, position papers, and practical demonstrations. Join us in advancing geospatial AI through representation learning!

For more details and submission guidelines, visit the GIScience 2025 conference website.

Workshop Organizer(s):

                                      Dr. Yu Liu, Peking University, liuyu@urban.pku.edu.cn

                                   Dr. Yang Yue, Hong Kong University of Science and Technology (Guangzhou), [yangyue@hkust-gz.edu.cn](<mailto:yangyue@hkust-gz.edu.cn>)