Speaker

Naoto Yokoya

Title

Open and Globally Reliable GeoAI

Abstract

This lecture presents our research toward open and globally reliable GeoAI that understands, reasons about, and reconstructs the real world from diverse and incomplete observations. Topics include global semantic mapping, multimodal disaster understanding, 3D reconstruction and scene generation from images and language, spatial reasoning with vision-language models, and confidence calibration for VLMs and AI agents. Through these examples, I will discuss how visual and spatial intelligence can become more generalizable, accessible, and trustworthy.

Bio

He is a Professor at The University of Tokyo and the Team Director of the Geoinformatics Team at the RIKEN Center for Advanced Intelligence Project. His research interests include remote sensing, computer vision, and machine learning, with applications to disaster management and environmental assessment. He has been recognized as a Clarivate Highly Cited Researcher every year since 2022.

Language

English (Offline)