The University of Texas at Austin
Spatially Explicit Artificial Intelligence Lab
We design better machine learning and artificial intelligence models by leveraging spatial knowledge and spatial inductive bias.
Who we are
About the Lab
The Spatially Explicit Artificial Intelligence Lab is directed by Dr. Gengchen Mai at the Department of Geography and the Environment, University of Texas at Austin. We work on Geospatial Artificial Intelligence (GeoAI), geo-foundation models, geographic knowledge graphs, and intelligent Earth observation, and we publish in top AI and GIScience venues such as NeurIPS, ICML, ICLR, ACM SIGIR, and IJGIS.
Our research is supported by the National Science Foundation, Amazon, and other sponsors, and our members have interned and worked at Google, Google DeepMind, Esri, Apple, and Amazon.
What’s happening
Latest News
- New Publication in IJGIS: Spatial CoT, Guiding LLM Reasoning with Spatial Core Concepts
- New publication: GAIR: Location-aware self-supervised contrastive pre-training with geo-aligned implicit representations
- Congratulations to Jielu Zhang and Zeping Liu on Receiving AAG 2026 Awards
- Dr. Junfeng Jiao Delivers a Talk on “Austin Digital Twin: AI-Powered Urban Simulation”
- One Paper Accepted by NeurIPS 2025
- Dr. Gengchen Mai Wins $300,000 National Science Foundation Research Grant
Every semester
GeoAI Talk Series
We invite speakers from academia and industry — Google Research, Google DeepMind, Esri, Stanford, and more — to share cutting-edge geospatial AI research.