Los Alamos National Laboratory

Los Alamos National Laboratory

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Capabilities

  • Earth and Space Sciences
  • Geophysics
  • Computer and Computational Sciences
  • Machine learning,
  • Data mining
  • Materials
  • Condensed matter
  • Granular materials

Expertise

Deep learning, Machine learning

Geophysics - Seismology, Tectonophysics, Induced seismicity

Geodesy - InSAR

Materials Science - Semiconductor physics, Nucleation

Education

Ph.D., Materials Science, University of Cambridge, UK, 2017

M.S., Materials Science, Ecole Normale Superieure, France, 2013

B.S., Materials Science, University of Paris Sud, France, 2011

 

LANL Positions

Research Scientist II, Geophysics Group (EES-17), 2019 - present

Postdoc, Geophysics Group (EES-17), 2017 - 2019

Graduate Research Assistant, Physics and Chemistry of Materials (T-1), Physics of Condensed Matter (T-4), Geophysics Group (EES-17), 2013 - 2017 (discontinuous)

 

Professional Societies

American Geophysical Union

 

Awards

LANL Director's postdoc fellowship (2017)

European Union ALIGHT grant (2013) – awarded as a PhD studentship

CHESS award (2013) – awarded by the University of Cambridge

Gonville & Caius award (2013) – awarded by the College

 

Publications

Bertrand Rouet‐Leduc, Claudia Hulbert, Ian W. McBrearty, Paul A. Johnson, "Probing Slow Earthquakes with Deep Learning", accepted, Geophysical Research Letters (2020)
 
Christopher X Ren, Aline Peltier, Valerie Ferrazzini, Bertrand Rouet-Leduc, PA Johnson, Florent Brenguier, "Machine Learning Reveals the Seismic Signature of Eruptive Behavior at Piton de la Fournaise Volcano", Geophysical Research Letters 47 (2020)
 
Rouet-Leduc, B., Hulbert, C. & Johnson, P.A. "Continuous chatter of the Cascadia subduction zone revealed by machine learning", Nature Geoscience 12 (2019)
 
Christopher X Ren, Omid Dorostkar, Bertrand Rouet‐Leduc, Claudia Hulbert, Dominik Strebel, Robert A Guyer, Paul Allan Johnson, Jan Carmeliet, "Machine learning reveals the state of intermittent frictional dynamics in a sheared granular fault", Geophysical Research Letters 46 (2019)
 
Claudia Hulbert, Bertrand Rouet-Leduc, Christopher X Ren, Jacques Riviere, David C Bolton, Chris Marone, Paul A Johnson, "Similarity of fast and slow earthquakes illuminated by machine learning", Nature Geoscience 12 (2019)
 
David C Bolton, Parisa Shokouhi, Bertrand Rouet‐Leduc, Claudia Hulbert, Jacques Rivière, Chris Marone, Paul A Johnson, "Characterizing acoustic signals and searching for precursors during the laboratory seismic cycle using unsupervised machine learning", Seismological Research Letters 90 (2019)

B. Rouet-Leduc, C. Hulbert, C.X. Ren, D.C. Bolton, C. Marone, P.A. Johnson, “Estimating Fault Friction From Seismic Signals in the Laboratory”, Geophysical Research Letters 45 (2018)

B. Rouet-Leduc, C. Hulbert, N. Lubbers, K. Barros, C.J. Humphreys, P. A. Johnson, “Machine learning predicts laboratory earthquakes”, Geophysical Research Letters 44 (2017)

B. Rouet-Leduc, C. Hulbert, K. Barros, T. Lookman, C.J. Humphreys, “Automatized convergence of optoelectronic simulations using active machine learning”, Applied Physics Letters 111 (2017)

B. Rouet-Leduc, K. Barros, T. Lookman, C. J. Humphreys, “Optimisation of GaN light emitting diodes and the reduction of efficiency droop using machine learning”, Scientific Reports 6, 24862 (2016)

D. Roehm, R.S. Pavel, K. Barros, B. Rouet-Leduc, et al., “Distributed Database Kriging for Adaptive Sampling (D2KAS)”, Computer Physics Communications 192, 138-147 (2015)

B. Rouet-Leduc, K. Barros, et al., “Spatial adaptive sampling in multiscale simulation”, Computer Physics Communications 185 (7), 1857-1864 (2014)

B. Rouet-Leduc, J.-B. Maillet, and C. Denoual, “The kinetics of heterogeneous nucleation and growth: an approach based on a grain explicit model”, Modelling and Simulation in Materials Science and Engineering 22 (3), 035018 (2014)

 
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