Benjamin Moyer

  • Program Year: 1
  • Academic Institution: University of Maryland, College Park
  • Field of Study: Computational Geophysics
  • Academic Advisor: Vedran Lekic
  • Practicum(s): Practicum Not Yet Completed
  • Degree(s):
    M.Sc. Geology, Wayne State University, 2021; B.A. Physics, Oakland University, 2019

Summary of Research

My primary research interest is to better characterize the subsurface of planetary bodies by leveraging modern computational resources in order to make inferences from a variety of geophysical datasets, particularly magnetic and gravitational anomaly data. Magnetic and gravity anomaly surveys are relatively inexpensive, provide wide coverage, and do not require physical coupling with the planetary body of interest. However, the constraints they provide result in a high degree of non-uniqueness, which has traditionally been removed by introducing assumptions about the interior. I choose to embrace this uncertainty within a trans-dimensional Bayesian framework. My efforts are focused on novel approaches to model proposal generation, greater incorporation of prior information, and improvements in computational efficiency through the aggressive exploitation of parallel algorithms, clever forward modeling computation, and GPU acceleration. These efforts will make the three-dimensional model domains tractable, enable the practical addition of other geophysical measurement types for simultaneous joint inversion, and facilitate the inversion of even larger datasets.

In addition to my primary research, I am interested in better characterizing the seismic noise produced by passenger trains. I seek to use the near-constant background 'hum' produced by Amtrak's Northeast Corridor to image the subsurface of the Eastern Seaboard through seismic interferometry.


Moyer, B. et al. (2023) 'Bayesian Inversion of Magnetic Data with Improvements from Constrained Low-Rank Approximation and Quasi-Random Sampling', in AGU Fall Meeting 2023. AGU.

Moyer, B. et al. (2022) 'Joint, Probabilistic Gravity and Magnetic Inversions for Planetary Exploration', in AGU Fall Meeting 2022. AGU.

Moyer, B. and Burdick, S. (2021) 'A Trans-dimensional Bayesian Approach to the Inversion of Gravitational and Structural Data', in AGU Fall Meeting Abstracts, pp. G33A-06.

Burdick, S., Moyer, B. and Boyce, A. (2021) 'Mantle Structure and Uncertainty from Transdimensional Bayesian P-wave Tomography in Alaska', in AGU Fall Meeting Abstracts, pp. T55A-0049.

Moyer, B. and Burdick, S. (2020) 'Rift Related Structure Near the Keweenaw Peninsula from a Novel Trans-dimensional Bayesian Inversion of Gravity and Structural Data', in AGU Fall Meeting Abstracts, pp. T041-0003.

Sikah, J. et al. (2020) 'Comparison of Field and Laboratory Measurements of Schist Anisotropy, Chester Dome, Vermont', in AGU Fall Meeting Abstracts, pp. DI029-0007.


Dean's Fellowship, University of Maryland, 2022-2023 recipient
Graduate Geology Merit Award, Wayne State University, 2020-2021 recipient