Among all forces of nature, earthquakes are considered one of the most devastating threats. They regularly cause enormous human and structural losses worldwide. Even though analysis and measurement methods have been continuously improved over the past decades, it is still not possible to make reliable predictions. While many indications of an increased earthquake probability are known, these do not allow for an exact prediction of the location and timing of catastrophic events.

In this project methods of AI are transferred to seismology. Machine Learning and Deep Learning approaches will be applied on earthquake data. For this purpose, new AI methods are developed, which can be used not only for the understanding of earthquakes but also for other natural disasters. The resulting know-how will also be used in teaching and research. Furthermore, it could be transferred to industrial applications.

Fellow Detail