Marine Denolle

• • Associate Professor
• • 206-111-1111
• • ATG 204
• Visit Marine's website

Education:
2014, PhD in geophysics – Stanford University (USA)
2008, Master en géophysique – Ecole Normale Superieure, Paris (France)
2006, License en géophysique – Ecole Normale Superieure, Paris (France)

Graduate Students:

• Yiyu Ni ( @ ESS): Cloud seismology, machine learning, data mining in the Pacific Northwest, earthquake early warning
• Tim Clements ( @ Harvard University): environmental seismology, monitoring groundwater and soil moisture using noise correlation functions; native cloud computing for seismology, computational seismology
• Jiuxun Yin ( @ Harvard University): observation and simulation of subduction-zone earthquakes, teleseismic backprojection, earthquake energy budget
• Seth Olinger ( @ Harvard University): cryoseismology – detection of ice-related seismic events, ice shelf rifting
• Congcong Yuan ( @ Harvard University): machine learning in seismology, wavefield simulations, theoretical ambient noise seismology, ambient noise monitoring

Marine uses large seismic data sets to investigate the dynamics of the Earth subsurface structure and earthquakes, using large-scale computing strategies and statistical learning.

Current Research:

Ground Motion Prediction: Long period strong ground motion in urban sedimentary basins. Surface waves observation and theory. Non-linear ground motions, near surface shaking damage and healing.

Earthquake Source Physics: Imaging of spatial and temporal variation of earthquake rupture parameters, in particular of shallow surface-rupturing events. Earthquake energy budget, body- and surface-wave radiated energy, stress drop, radiation efficiency, fracture energy. Focus on surface ruptures. Earthquake co-seismic damage.

Environmental Seismology: monitoring of subsurface hydrology using ambient seismic field, impacts of extreme events (droughts, wet climatic events).

High-performance Seismology: Numerical tools to deal with TB-PB size data sets for ambient noise monitoring and imaging. Open-source software in Python and Julia. HPC and cloud computing. Machine learning for seismology.