Current research projects and academic contributions in data science and urban analytics.
Developing novel visualization techniques for complex hypergraph structures with applications in urban data analysis and network science. This research focuses on creating intuitive visual representations of high-dimensional relationships in spatial data, particularly for understanding urban commercial patterns and social dynamics.
Comprehensive analysis of Points of Interest (POI) data for understanding urban spatial patterns and commercial dynamics. This study examines the relationship between commercial density, urban form, and social activity patterns across multiple metropolitan areas.
Investigating spatial relationships and network structures in urban environments using graph theory and machine learning approaches. The research develops new methodologies for analyzing complex spatial networks and their evolution over time.