SECCHI MAURICIO ANDRES

PhD Project Summary:

I am a geophysicist specializing in artificial intelligence and computational modelling applied to geosciences. During the first year of my PhD, my research focused on physics-based numerical modelling, inverse methods, and AI-driven surrogate models for debris-flow dynamics, parameter estimation, and landslide hazard assessment.

During the second year, the project will expand toward advanced seismic imaging techniques for the characterization of the shallow subsurface in landslide-prone areas. The aim is to combine innovative seismic methods, numerical wave-propagation modelling, inversion, and AI to reconstruct subsurface structures and identify zones of weakness and instability.

During the third year, these components will be integrated into a unified and robust framework combining surface-process modelling, subsurface seismic imaging, inversion, monitoring, and artificial intelligence. The final objective is to develop a comprehensive computational product for landslide characterization, monitoring, and hazard assessment.

The two attached images schematically represent the two main components of the project: AI-supported seismic imaging of the shallow subsurface and AI-assisted landslide/debris-flow modelling and monitoring.