GeoDI Lab members attended the 2024 International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL 2024)

GeoDI Ph.D. student, Sheng Wang, gave a talk entitled Edge Activating Module: Learning edge-to-edge features for mobility flow generation for the 7th ACM SIGSPATIAL International Workshop on AI for Geographic Knowledge Discovery (GeoAI'24).

Sheng Wang presenting the research on edge activating module in GeoAI'24
 

The GeoAI'24 workshop was hosted by scholars across the domain of GIScience and AI, with a continued combination of artificial intelligence, spatiotemporal data computing, and geographic research since its first launch in 2017.

Advances in artificial intelligence, hardware accelerators, and data processing architectures continue to reach the geospatial information sciences, with a transformative impact on many societal challenges. Recent breakthroughs in deep learning have brought forward an automated capability to learn representative features from massive and complex data, including text, images, and videos. In tandem, rapid innovations in sensing technologies support the collection of geospatial data in even higher resolution and throughput, supporting the observation, mapping, and analysis of different events/phenomena over the Earth’s surface with unprecedented detail. Combined, these developments are offering the potential for breakthroughs in geographic knowledge discovery, impacting decision-making in areas such as humanitarian mapping, intelligent transport systems, urban expansion analysis, health data analysis and epidemiology, the study of climate change, handling natural disasters, the general monitoring of the Earth’s surface, and achieving sustainability.