Dr Sarah Bentley

VC Fellow

Department: Mathematics, Physics and Electrical Engineering

I graduated from Durham University with an MMath in 2013. After about in a year in industry working on a geometry system which underlies computer aided design software, I began a PhD at the University of Reading in 2015. As part of the space weather group inside the Meteorology depatrment, the focus of this work was to understand and predict the driving of magnetosphere-scale ULF waves by the solar wind in order to use in space weather models. I stayed on at Reading as a post-doctoral researcher in order to further this work and in 2020 joined Northumbria as a Vice-Chancellor's Fellow. In addition to continuing the various directions of my research, this provides me with the opportunity to develop my teaching and research proposal writing skills.

Due to my mixed backgrounds in space physics, meteorology, maths and geometry, I have a wide range of interests. I am still interested in the prediction of ULF waves and the resulting radial diffusion in Earth's radiation belts. However, I am also investigating a variety of techniques drawn from other fields, such as machine learning/artificial intelligence, optimisation and stochastic/probabilistic approaches to this problem, and how geometric structures combined with data assimilation can be used to efficiently model geomagnetic phenomena that underpin the co-ordinate systems used in space weather prediction.

For more information about me and my work, please visit my personal page. On this site you will also be able to find current PhD opportunities and more about how I supervise students.

Email Sarah

Key Publications

Please visit the Pure Research Information Portal for further information
Automatic Encoding of Unlabeled Two Dimensional Data Enabling Similarity Searches: Electron Diffusion Regions and Auroral Arcs, Smith, A., Rae, J., Stawarz, J., Sun, W., Bentley, S., Koul, A. Jan 2024, In: Journal of Geophysical Research: Space Physics
A New Four‐Component L*‐Dependent Model for Radial Diffusion Based on Solar Wind and Magnetospheric Drivers of ULF Waves, Murphy, K., Breneman, A., Sandhu, J., Angelpoulos, V., Kellerman, A., Watt, C., Daggitt, T., Wygant, J., Horne, R., Tian, S., Bentley, S., Glauert, S., Olifer, L., Mann, I., Rae, J., Ozeke, L., Halford, A. Jul 2023, In: Space Weather
Using Machine Learning to Diagnose Relativistic Electron Distributions in the Van Allen Radiation Belts, Killey, S., Rae, J., Chakraborty, S., Smith, A., Bentley, S., Bakrania, M., Wainwright, R., Watt, C., Sandhu, J. 2023, In: Royal Astronomical Society Techniques and Instruments
Imaging the magnetosphere-ionosphere system with ground-based and in-situ magnetometers, Murphy, K., Bentley, S., Miles, D., Sandhu, J., Smith, A. 2022, Magnetospheric Imaging, Elsevier
RAS Specialist Discussion Meeting report, Coxon, J., Aruliah, A., Bentley, S., Shore, R. 1 Feb 2022, In: Astronomy & Geophysics
Temporal variability of quasi-linear pitch-angle diffusion, Watt, C., Allison, H., Bentley, S., Thompson, R., Rae, I., Allanson, O., Meredith, N., Ross, J., Glauert, S., Horne, R., Zhang, S., Murphy, K., Rasinskaitė, D., Killey, S. 13 Oct 2022, In: Frontiers in Astronomy and Space Sciences
Pro-L* - A Probabilistic L* mapping tool for ground observations, Thompson, R., Morley, S., Watt, C., Bentley, S., Williams, P. 20 Feb 2021, In: Space Weather
The implications of temporal variability in wave‐particle interactions in Earth's Radiation Belts, Watt, C., Allison, H., Thompson, R., Bentley, S., Meredith, N., Glauert, S., Horne, R., Rae, I. 16 Jan 2021, In: Geophysical Research Letters
Particle‐in‐Cell Experiments Examine Electron Diffusion by Whistler‐Mode Waves: 2. Quasi‐Linear and Nonlinear Dynamics, Allanson, O., Watt, C., Ratcliffe, H., Allison, H., Meredith, N., Bentley, S., Ross, J., Glauert, S. Jul 2020, In: Journal of Geophysical Research
Random Forest Model of Ultralow-Frequency Magnetospheric Wave Power, Bentley, S., Stout, J., Bloch, T., Watt, C. Oct 2020, In: Earth and Space Science

PGR Supervision

Kendra Gilmore Characterising Earth's Magnetic Field with Graph Neural Networks Start Date: 01/10/2022

Qualifications

PhD July 18 2019
Mathematics June 28 2013

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