
Career
- 2021-present: Director of Studies in Physics, Homerton College, University of Cambridge
- 2020-present: Junior Research Fellow, Homerton College, University of Cambridge
- 2016-2020: PhD, DAMTP, University of Cambridge
- 2015-16: MSci Physics, Gonville and Caius, University of Cambridge
- 2012-15: BA Natural Sciences, Gonville and Caius, University of Cambridge
Research
Amelia is a member of the Department of Applied Mathematics and Theoretical Physics Relativity and Gravitation research group. Her current research interests are axion and gravitational wave (GW) signatures from cosmic strings, and GW signatures from dark matter around black holes. She is a developer of the adaptive mesh numerical relativity code, GRChombo (https://www.grchombo.org/).
Publications
Radiation from global topological strings using adaptive mesh refinement: Massive modes
– Physical Review D
(2023)
107,
043507
(doi: 10.1103/physrevd.107.043507)
Radiation from Global Cosmic Strings using adaptive mesh refinement
– The Sixteenth Marcel Grossmann Meeting
(2023)
1891
(doi: 10.1142/9789811269776_0148)
Lessons for adaptive mesh refinement in numerical relativity
– Classical and Quantum Gravity
(2022)
39,
135006
(doi: 10.1088/1361-6382/ac6fa9)
Radiation from Global Topological Strings using Adaptive Mesh Refinement: Methodology and Massless Modes
– Physical Review D: Particles, Fields, Gravitation and Cosmology
(2022)
105,
063517
(doi: 10.1103/physrevd.105.063517)
GRChombo: An adaptable numerical relativity code for fundamental physics
– Journal of Open Source Software
(2021)
6,
3703
(doi: 10.21105/joss.03703)
Training Neural Machine Translation (NMT) Models using Tensor Train
Decomposition on TensorFlow (T3F)
(2019)
Black holes, gravitational waves and fundamental physics: A roadmap
– Classical and Quantum Gravity
(2019)
36,
143001
(doi: 10.1088/1361-6382/ab0587)
Using computing models from particle physics to investigate dose-toxicity correlations in cancer radiotherapy
– Journal of Physics: Conference Series
(2017)
898,
072048
Applying physical science techniques and CERN technology to an unsolved problem in radiation treatment for cancer: the multidisciplinary 'VoxTox' research programme.
– CERN Ideasq J Exp Innov
(2017)
1,
3
(doi: 10.23726/cij.2017.457)
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