Yoshihide Sekimoto

Yoshihide Sekimoto is a researcher with extensive contributions to computer science, geospatial engineering, and urban planning. His work focuses on leveraging deep learning, remote sensing, and GIS data for infrastructure analysis, human mobility modeling, and disaster response systems.

• Specializes in road damage detection using federated learning and computer vision
• Develops synthetic human mobility datasets for urban and disaster scenarios
• Integrates spatio-temporal modeling with graph networks for transportation systems
• Applies AI to environmental monitoring (e.g., satellite wind resolution)

His recent publications highlight collaborations on 3D building reconstruction, public transit visualization, and land price estimation via street view images. Articles trends include multi-modal data fusion, cross-country infrastructure analysis, and agent-based simulations for urban dynamics.