Recent Advances in Geospatial Machine Learning

Webinar Speaker:

Loïc Landrieu

Affiliation:

ENPC

  • 21 January 2026
  • 12:00 PM UTC
  • Sponsored by GRSS
  • IADF - TC Webinar
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About the Webinar

Geospatial machine learning has emerged as a compelling testing ground for modern computer vision and machine learning algorithms. In this talk, I will present recent progress in massively multimodal self-supervised learning for Earth observation, including large-scale pretraining across heterogeneous sensor modalities, unified representations for optical, radar, and elevation data, and scalable training strategies I will then discuss our latest work on visual geolocation, covering both standardized benchmarking and diffusion-based generative models that output spatial probability maps.

 

About the Speaker

Loic Landrieu is a research scientist at ENPC and a Senior Hi! PARIS Fellow, working on machine learning for large-scale geospatial analysis. He received his PhD from École Normale Supérieure (ENS) Paris in 2016. Active in both remote sensing and computer vision, he serves as Area Chair for CVPR, ECCV, 3DV, and IGARSS, and sits on the editorial board of the ISPRS Journal while co-chairing the ISPRS Working Group on Temporal Data Understanding. He was co-program Chair of the 2022 ISPRS Congress, the CVPR EarthVision workshop, and the first REO workshop at NeurIPS 2025.

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