UQGNN: Uncertainty Quantification of Graph Neural Networks for Multivariate Spatiotemporal Prediction (ACM SIGSPATIAL 2025)
highway2vec: representing OpenStreetMap microregions with respect to their road network characteristics
Busyness Graph Neural Network (BysGNN): A framework for accurate Point-of-Interest visit forecasting using dynamic graphs that capture spatial, temporal, semantic, and taxonomic contexts. Presented at ACM SIGSPATIAL 2023, this repository includes code, baselines, and experiments.
Reproduction artefact for the SIGSPATIAL '26 paper "Knowledge Channels for LLM Agents on Remote-Sensing Tasks"
Ray Resilience: an accountable GeoAI system for place-based disaster intelligence — resilience intelligence for every place. WebGIS/smartphone PWA + Steward Harness. OASIS @ ACM SIGSPATIAL 2026 Track A.
Developed an optimized solution to the point-polygon query program mentioned by the ACM SIGSPATIAL CUP 2013. Showed differences between naive solution and my solution. Achieved 100% accuracy for both 'INSIDE' and 'WITHIN n' queries.
Project page for our ACM SIGSPATIAL 2024 paper "Critical Features Tracking on Triangulated Irregular Networks by a Scale-Space Method".
Project page and code for "ImplicitTerrainV2: Wavelet-Guided Spatially Adaptive Neural Terrain Representation" (ACM SIGSPATIAL 2026).
Project page and code for "Rethinking Amortized Neural Representations for High-Resolution Terrain Elevation Data" (ACM SIGSPATIAL 2026).
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