This online meeting of the IAG GGOS Joint Study Group on AI for GNSS Remote Sensing (open to non-members) brings together researchers and practitioners to discuss recent advances in artificial intelligence and machine learning applied to GNSS-based Earth observation. The program covers AI-driven approaches for atmospheric and ionospheric sensing, tropospheric modeling, uncertainty quantification, and GNSS reflectometry.
Agenda:
- 14:00–14:15 — Nikolina Govedarica (IBM Corporation)
Agentic AI – Action-Driven Intelligence - 14:15–14:30 — Cuixian Lu (Wuhan University)
GNSS Atmospheric Sounding Using Deep Learning - 14:30–14:45 — Peng Yuan (GFZ)
AI-Enhanced Vertical Modeling of Tropospheric Products - 14:45–15:00 — Saeid Haji-Aghajany (Wrocław University of Environmental and Life Sciences)
Remote Sensing Techniques for AI-Based Tropospheric Analysis and Weather Forecasting - 15:00–15:15 — Randa Natras (DLR)
Uncertainty Quantification in ML-Based Models Applied to Ionosphere Forecasting - 15:15–15:30 — Lei Liu (University of Michigan, Ann Arbor)
Ionosphere Remote Sensing Using GNSS Measurements - 15:30–15:45 — Hamed Izadgoshasb (Sapienza University of Rome / GFZ)
Explainable CYGNSSnet for Global GNSS-Reflectometry Soil Moisture - 15:45–15:50 — Wrap-up and final discussions
