Yuta Sato
Yuta Sato is a PhD candidate at the Geographic Data Science Lab, University of Liverpool, focusing on graph representation learning for evaluating sustainable urban developments (e.g., 15-Minute City).
He is the lead maintainer of City2Graph, an open-source Python library that transforms geospatial datasets into heterogeneous graphs for Graph Neural Networks.
Yuta received a Master's degree in Geographic Data Science from the London School of Economics (LSE). He has four years of professional experience as a cybersecurity solution architect at Nissan Motor Corporation Ltd. and as a spatial data scientist at Spatial Pleasure Inc.
Session
This workshop introduces Graph Neural Networks (GNNs) for geospatial practitioners. Using open-source Python tools including PyTorch Geometric and City2Graph, participants will learn how to transform urban geospatial data into network structures and apply GNNs to model complex spatial relations.