Machine learning for earthquake risk assessment

Funding agency: National Research and Development Agency (ANID)

Grant: FOVI 230030 (2023-2024)

Principal Investigator: Rodrigo Astroza

Co-Principal Investigators: Jawad Fayaz, Saeed Eftekhar Azam, Yong Li, Carla Vairetti, Ramiro Bazaez, Gaston Fermandois

The project aims to conduct pioneering research for earthquake risk assessment, integrating experimental data measured during previous seismic events and information generated through nonlinear finite element models, with advanced statistical techniques from the field of machine learning and probabilistic methods for uncertainty quantification and propagation. The goal is to estimate regional seismic hazard in Chile and develop tools for damage identification in structures subjected to earthquakes.

The project is comprised of a network of Chilean researchers from the Universidad de los Andes and the Universidad Federico Santa Maria, along with international researchers from the University of Alberta, University of Exeter, and University of New Hampshire.