Assistant Professor of Geophysics
Office: 127A SR1
- Inversion of geophysical data set (e.g., gravity, gravity gradiometry, magnetics, DC, IP, MT, EM, seismic traveltime) constrained by geological prior information.
- Joint inversion of multiple geophysical data sets based on structural similarity and prior petrophysical measurements.
- Sparse inversion using L1 and L0 norm regularization.
- Magnetization vector inversion with clustering constraints.
- Machine learning, such as neural networks and deep learning, applied to geophysical problems.
- Sparse signal processing of geophysical data.
- Melo, A., J. Sun and Y. Li, 2017, Geophysical inversions applied to 3D geology characterization of an iron oxide copper gold deposit in Brazil: Geophysics, 82(5), K1-K13.
- Sun, J., and Y. Li, 2017, Joint inversion of multiple geophysical and petrophysical data using generalized fuzzy clustering algorithms: Geophys. J. Int., 208(2), 1201-1216.
- Li, Y., and J. Sun, 2016, 3D magnetization inversion using fuzzy c-means clustering with application to geology differentiation: Geophysics, 81(5), J61-J78.
- Sun, J., and Y. Li, 2016, Joint inversion of multiple geophysical data using guided fuzzy c-means clustering: Geophysics, 81(3), ID37-ID57.
- Sun, J., and Y. Li, 2015, Multidomain petrophysically constrained inversion and geology differentiation using guided fuzzy c-means clustering: Geophysics, 80(4), ID1-ID18.
- Sun, J., and Y. Li, 2014, Adaptive Lp inversion for simultaneous recovery of both blocky and smooth features in a geophysical model: Geophys. J. Int., 197(2), 882-899.