Yannik BehrData Science Specialist
AI and Advanced Analytics
Yannik is a geophysicist and member of the AI and Advanced Analytics team in the Datascience and Geohazards Monitoring department. He has a keen interest in combining physics-based and statistical models and detecting anomalies in our observational data using machine learning. Yannik applies these interests to his work on seismic and volcano monitoring. His past work included ambient seismic noise tomography, seismic beamforming, and Earthquake Early Warning in New Zealand, California, and Europe.
- MSc, Geophysics
- PhD, Seismology
Areas of expertise
- Geophysics: Seismology
- Geophysics: Mathematical inversion techniques
- Geophysics: Seismic tomography
- Geophysics: Real-time seismological monitoring
- Geophysics: Real-time seismological analysis
- Geophysics: Data analysis
- Geophysics: Data management
- Geophysics: Applications of statistics
- Geophysics: Time series techniques for data analysis
- Geophysics: Volcanic surveillance
- Geophysics: Strong motion accelerogram analysis
- Geophysics: Seismograph array analysis
- Information Technology: Shell scripting
- Information Technology: Python
- Geophysics: Noise interferometry
- Geophysics: Earthquake Analysis - SeisComP3
- Information Technology: Machine Learning
- Information Technology: C/C++ programming
See all publications
- Continuous estimates of heat emission at Mt. Ruapehu using the Unscented Kalman Smoother, Journal of applied volcanology 12(1): article 1. DOI: 10.1186/s13617-022-00125-y.
- Towards real-time probabilistic ash deposition forecasting for New Zealand, Journal of applied volcanology 11(1): article 13. DOI: 10.1186/s13617-022-00123-0.
- Anatomy of an earthquake early warning (EEW) alert : predicting time delays for an end-to-end eew system, Seismological Research Letters 86(3): p. 1-11. DOI: 10.1785/0220140179.
- Source directionality of ambient seismic noise inferred from three-component beamforming, Journal of Geophysical Research. Solid Earth 118(1): p. 240-248. DOI: 10.1029/2012JB009382.
- The benefit of hindsight in observational science: retrospective seismological observations, Earth and Planetary Science Letters 345-348: p. 212-220. DOI: 10.1016/j.epsl.2012.06.008.
- ObsPy : a python toolbox for seismology, Seismological Research Letters 81(3): p. 530-533. DOI: 10.1785/gssrl.81.3.530.