My work includes Machine Learning applications for geophysics, seismic and acoustic event monitoring, and planetary exploration
Machine learning
2023: Conflict monitoring using seismic timeseries segmentation
We developed model to detect and pick seismic and sound signals from explosions during the Ukraine-Russia war by training a CNN autoencoder with self-attention.
2022: Predicting sound amplitude with deep learning
We trained a deep CNN to compute the sound amplitudes from explosions by mapping atmospheric winds sound attenuation at ground level.
2021: Detection of earthquakes from satellite data using machine learning
We built an automatic detector and arrival time picker of large earthquake signals in GNSS satellite data using Ranfom Forests.
Event monitoring
2023: Seismic and acoustic analysis of the largest minequake in the Nordics
We were able to retrieve seismic source parameters from the sound signature of a large minequake.
2023: Seismic monitoring of the Ukraine-Russia war
We developed a model to perform seismic and infrasound monitoring of the 2022 Russia-Ukraine war in real time.
2023: Atmospheric waves and global seismoacoustic observations of the January 2022 Hunga eruption, Tonga
We analyzed the seismic, acoustic, and satellite data after the 2022 Hunga eruption, the largest volcanic eruption in recorded history.