Paper Workshop on “Organizations and Urban Inequality”

We are pleased to share that PhD student Rui Deng’s work, “Improving the Computational Efficiency and Explainability of GeoAggregator” has been accepted as a Short Paper at the ACM SIGSPATIAL GeoAI Workshop. Rui Deng, together with fellow PhD student Xinyi Yuan, travelled to Minneapolis, USA, from 3–6 November to attend the event.

In his 7-minute presentation, Rui introduced GeoAggregator—a lightweight, scalable, and highly effective Transformer model developed for Geospatial Tabular Data (GTD). The paper outlines both the model design and its efficient Python implementation, GA-Sklearn, which is now publicly available for fast and accurate regression modelling on GTD datasets.

This research, co-authored with Dr. Ziqi Li (FSU) and Dr. Mingshu Wang, reflects the group’s ongoing advancements in GeoAI and Spatial Data Science, and strengthens our presence within the broader computer science and GeoAI communities. During the conference, Rui and Xinyi engaged in wide-ranging discussions with researchers across the United States, helping to foster new academic connections and future collaboration opportunities.