Postdoctoral research associate, Department of Geosciences, Princeton University, 2008-2011
Ph.D. Geophysics, Swiss Federal Institute of Technology (ETH Zurich), 2008
M.Sc. Physics, Swiss Federal Institute of Technology (ETH Zurich), 1998
Research Interests
Professor Daniel Peter’s research interests are related to computational seismology and geophysical inverse problems. He focuses on enhancing numerical 3D wave propagation solvers for seismic tomography, particularly for very challenging complex regions and media. To this end, he exploits and implements high-performance computing (HPC) algorithms into 3D wave propagation solvers to better investigate such regions numerically, with the potential to highly improve resolution and reliability in seismic imaging. These techniques and solvers can be applied to hydrocarbon exploration as well as regional- and global-scale seismic tomography. Prof. Peter’s research at KAUST will focus on the development of new algorithms in seismic wave propagation and applications in seismic tomography across all scales.
Selected Publications
Rietmann, M., P. Messmer, T. Nissen-Meyer, D. Peter, P. Basini, D. Komatitsch, O. Schenk, J. Tromp, L. Boschi and D. Giardini, 2012. Forward and adjoint simulations of seismic wave propagation on emerging large-scale GPU architectures, SC ’12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis, Article No. 38
H.J. Zhu, E. Bozdag, D. Peter and J. Tromp, 2012. Structure of the European upper mantle revealed by adjoint tomography, Nature Geoscience, 5, 493-498, doi:10.1038/NGEO1501.
Peter, D., D. Komatitsch, Y. Luo, R. Martin, N. Le Goff, E. Casarotti, P. Le Loher, F. Magnoni, Q. Liu, C. Blitz, T. Nissen-Meyer, P. Basini and J. Tromp, 2011. Forward and adjoint simulations of seismic wave propagation on unstructured hexahedral meshes, Geophys. J. Int., 186 (2), 721-739.
Savage, B., D. Peter, B.M. Covellone, A.J. Rodgers and J. Tromp, 2011. Next Generation, Waveform Based Three-Dimensional Models and Metrics to Improve Nuclear Explosion Monitoring in the Middle East, in Proceedings: 33rd Monitoring Research Review (MRR 2011), 1-17, p. 161-167
Tromp, J., Y. Luo, S. Hanasoge and D. Peter, 2010. Noise Cross-Correlation Sensitivity Kernels, Geophys. J. Int., 183 (2), 791-819