Sophie Giffard

Sophie Giffard is a Researcher at the ISTerre Laboratory, Université Grenoble Alpes, and a visiting researcher at Columbia University via a Fulbright Fellowship (2025-2026). Her work focuses on machine learning applications in natural hazards, geophysics, and climate science. She leads projects like the ANR JCJC Project EDAM (2024-2028) for machine learning-based geomorphological analysis and the MIAI MOHAIR chaire (2025-2029) on remote sensing and hazards monitoring. Previously, she held a postdoctoral position at the University of Colorado Boulder (2018-2019) and completed her PhD on cardiac modeling at Inria Sophia-Antipolis (2017).

Research Interests: Machine learning for seismic and landslide detection, satellite image analysis, climate informatics, and medical image analysis. Her projects address challenges in natural hazard monitoring, geophysical data interpretation, and personalized cardiac modeling.

Publications: Over 20 peer-reviewed articles, including breakthroughs in displacement estimation via deep learning, slow-slip event detection using graph neural networks, and hurricane track forecasting. Notable work includes the GeoFlowNet model for sub-pixel displacement analysis and the MicroFlow framework for seismic event detection.

Awards: Received the Best Paper Award at the 2017 FIMH conference for contributions to cardiac electrophysiology modeling.

Advising: Actively mentors PhD/MSc students in machine learning applications for geoscience and climate science. Current openings for motivated researchers in AI-driven hazard monitoring and remote sensing.