Last info 17.12.2020

 

Curriculum Vitae

 

Research Interest

• natural hazards and seismologyambient noise
• instrumentation and geophysical monitoring
• applying machine learning tools in the scope of earth sciences
• source detection in large data sets

 

Publications, invited talks and conference contributions 

• Novoselov, A. , Bokelmann, G., Hein, G., Balazs, P., Source Separation of Seismically Induced Signals, Summer of Machine Learning in Skoltech, Moscow, 2020
• Novoselov, A., Bokelmann, G., Hein, G., Balazs, P., Separation and denoising of seismically-induced ground-motion signals with dual path residual neural network architecture, poster at the AGU Fall Meeting 2020 San Francisco
• Bokelmann, G., Hein, G., Extracting robust splitting measurements for the AlpArray using the splitting intensity method, Chat at the EGU 2020, Vienna
• Hein, G., Novoselov, A., Fuchs, F., Bokelmann, G., Matching seismic activity with potential sources using machine Learning, Chat at the EGU 2020, Vienna
• Novoselov, A., Hein, G., Bokelmann, G., Fuchs, F., TraML: separation of seismically-induced ground-motion signals with Autoencoder architecture, Chat at the EGU 2020, Vienna
• Hein, G., Bokelmann, G., the AlpArray Working Group, Extracting robust splitting measurements from the splitting intensity method, poster at the 2nd AlpArray Meeting, Frankfurt 2019
• Hein, G., Löberich, E., Bokelmann, G., Automatic Shear-Wave Splitting Analysis with SplitWave, presentation at the AlpArray Seismic Anisotropy Workshop, Uni Wien, 2019
• Stähler, S. C., Schmid-Aursch, M.C., Hein, G., Mars, R., A self-noise model for the german Depas OBS pool, Seismological Research Letters
• Hein, G., A noise model for the german Depas OBS pool, New advances in Geophysics: The Future of Passive Seismic Axquisition, The Royal Society of Edinburgh 11.11.2018
• Further information here

 

Links

ZAMG