- About Me
Ph.D., 2008, Geophysics, California Institute of Technology (Caltech).
B.S., 2001, Geophysics, University of Science and Technology of China (USTC).
Min Chen is a computational seismologist. Her research interests lie in developing and applying numerical tools harnessing the power of high performance computing for seismic full waveform inversion, imaging, and interpretation. Her research aims to better understand plate tectonic processes and earthquake rupture processes using high-resolution seismic images.
Min Chen is currently an assistant professor at Michigan State University, jointly appointed by the Department of Computational Mathematics, Science and Engineering and the Department of Earth and Environmental Sciences. She received her Ph.D. from California Institute of Technology. She then was a postdoctoral research associate at Massachusetts Institute of Technology and subsequently at Rice University. She later was a research scientist at Rice University under NSF grant #1345096.
- MSU Computational Seismology Lab
Scientific Leader: Dr. Min Chen
MSU Computational Seismology Lab works on analyzing, numerical modeling, and full waveform inversion of seismic array data from various sources, such as earthquakes, explosions, and ambient noise sources. Our goal is to better understand dynamic processes of the Earth on different time and spatial scales.
- Research Interests
• Full Waveform Inversion Based on Spectral-element & Adjoint Methods
• Mantle & Tectonic Processes in East Asia (Tibet), SW Europe, & South America
• Nature of Deep-focus Earthquakes in Subduction Zones
• Earthquake Source Imaging & Inversion
- Data Science and Computational Seismology Lab
Research in developing and applying data analytics and computational algorithms to enable fast and high-fidelity multi-scale seismic imaging, with emphasis on dynamic monitoring the near-subsurface structure of the Earth. Potential projects include but are not limited to assimilating seismic data sets derived from passive, active, and ambient noise sources to image, monitor, and model (1) the spatial and temporal changes of active seismic and volcanic regions and (2) the interactions of water, life, soil, and rock in the Earth's critical zone. Candidates with strong background in seismic imaging and high-performance computing will be given priority. Experience with large data sets, machine learning, and GPU programming are desired. The successful candidate will be working with Dr. Min Chen. Preferred start date no later than September 1st, 2019, earlier if possible.
Applicants must specify an area of focus and faculty they want to work with in the cover letter of their application. Applicants must provide a Research Statement, Teaching Statement, Curriculum Vita, and three references. Applicants must apply through the MSU online system. http://careers.msu.
- Selected Publications
Ribeiro, J., Stern, R., Fernando, M., Woodhead, J., Chen, M., and Ohara, Y. (2017), An Indian mantle outflow underneath the southern Mariana convergent plate margin?, Earth and Planetary Science Letters, doi:10.1016/j.epsl.2017.08.022. [link]Chen, M., Niu, F., Tromp, J., Lenardic, A., Lee, C.-T. A., Cao, W., and Ribeiro, J. (2017), "Lithospheric Foundering and Underthrusting Imaged Beneath Tibet", Nature Communications, doi:10.1038/ncomms15659. [link] [PDF download] [News release]Liu, Y., Niu, F., Chen, M., and Yang, W. (2017), "3-D Crustal and Uppermost Mantle Structure Beneath NE China Revealed by Ambient Noise Adjoint Tomography", Earth and Planetary Science Letters, doi:10.1016/j.epsl.2016.12.029. [link]Xing, G., Niu, F., Chen, M., Yang, Y. (2016), "Effects of Shallow Density Structure on the Inversion for Crustal Shear Wavespeeds in Surface Wave Tomography", Geophysical Journal International, doi: 10.1093/gji/ggw064. [link]Chen, M., Niu, F., Liu, Q., and Tromp, J. (2015), "Mantle-driven Uplift of Hangai Dome: New Seismic Constraints from Adjoint Tomography", Geophys. Res. Lett., 42, doi:10.1002/2015GL065018. [link]
No courses for this academic year.
Click "Teaching" link to see past courses.