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Professional History

  • Schmidt AI in Science Fellow

    • Department of Earth Sciences, University of Oxford

    • Associate Research Fellow of Reuben College

    • Investigating probabilistic AI methods for inner core seismology

  • Machine Learning Engineer

    • Earth Rover Program

    • Developing machine learning tools for the analysis of seismic waves probing soil structure.

  • Postdoctoral Fellow in Seismology

    • Research School of Earth Sciences, Australian National University

    • Investigating the sedimentary structure of Australia using novel passive seismic methods.

    • Investigating regularisation approaches to obtain sharp boundaries in geophysical imaging

  • Postdoctoral Research Associate in Seismology

    • Department of Earth Sciences, University College London

    • Investigating high-dimensional Bayesian methods for imaging the deep mantle plume beneath the Azores using data from the UPFLOW expedition.

  • Machine Learning Intern

    • KageNova Ltd.

    • Investigating spherical convolutional neural networks for applications in virtual reality.

Education

  • PhD Data Intensive Science (Seismology and Cosmology), UCL

    • From Dark Matter to the Earth’s Deep Interior: There and Back Again

    • Supervised by Prof Ana Ferreira and Prof Thomas Kitching

    • Submitted 30/9/22, Defended 6/12/22, Awarded 28/01/2023

  • MSci Geophysics, UCL

    • First Class Honours

    • Independent Project: Rayleigh wave ellipticity inversion for crustal velocity structure

    • Won UCL Matthew’s Prize for Excellence in Geophysics

Awards and Prizes

  • Schmidt AI in Science Research Fellowship, University of Oxford — £150,000

  • ANU ECR Travel Grant, 2024 — AU$3000

  • ANU RSES Director’s Award for Strategic Research, 2023 — AU$6000

  • AGU Fall Meeting Outstanding Student Presentation Award, 2021 — US$250

  • UCL Matthew’s Prize for Excellence in Geophysics, 2018

  • UCL Earth Sciences Prize for Best MSci Poster Presentation, 2018

Open Source Code Packages

  • CoFI: Framework for geophysical inverse problems

  • neighpy: Python implementation of the Neighbourhood Algorithm for Bayesian Inference

  • octo: Python implementation of overcomplete tomography inversion

  • aussedthick: Estimating the sediment thickness across Australia

  • stringgen: Fast Python emulations of cosmic string maps using wavelet phase harmonics

  • mmtdt: C++ code for cosmological mass-mapping using trans-dimensional MCMC

  • pxmcmc: Python package for proximal MCMC

  • greatcirclepaths: Python package for discretising great circle paths for different spherical sampling theorems

Teaching

  • Earth Science Research Project (ANU)

    • Postgraduate

    • Expert Examiner for a Master’s research project entitled Developing a deep-learning model to detect and measure the Earth’s inner-core sensitive waves.

    • Selected as Expert Examiner for my understanding of machine learning in seismology.

    • Parts of the thesis have since been published in JGR:SE.

  • Machine Learning with Big Data (UCL)

    • Postgraduate

    • >100 students from a range of physics, computer science and data science Masters programs

    • Teaching in the form of hands-on tutorials, and coursework and exam marking

    • Leading and coordinating team of demonstrators

  • Seismology II (UCL)

    • 3rd year undergraduate

    • 8–13 students

    • Teaching in the form of guest lectures, practical sessions, coursework marking and project supervision

  • Field Geophysics (UCL)

    • 3rd year undergraduate

    • 8–13 students

    • Teaching in the form of guided practicals, fieldwork and project supervision

  • MATLAB for Earth Sciences (UCL)

    • 1st year undergraduate

    • >70 students

    • Developed the course from scratch

    • Teaching in the form of short lectures, practical sessions and coursework marking

Student Supervision

  • Kaustubh Raj. Future Research Talent Student, RSES ANU

    • Using receiver function autocorrelations to estimate sedimentary thickness of Australia.

    • Co-supervised with Dr Caroline Eakin

  • Mansi Baguant. MSc Knowledge, Information and Data Science, UCL

    • Deep earthquake classification using deep learning.

    • Co-supervised with Prof Ana Ferreira and Dr Maria Tsekhmistrenko

  • Mag Marin Adrian. MSci Geophysics, UCL

    • Towards building 3D global seismic tomography models using proximal methods.

    • Co-supervised with Prof Ana Ferreira and Dr Matthew Price

Fieldwork

  • SNAKEY seismic network service run, South Australia

    • Servicing of seismic stations and initial data recovery around Kangaroo Island, Lake Eyre and the York Peninsula.

  • Land seismometer deployment, Azores

    • Emergency deployment of seismic stations in the Azores archipelago in response to a swarm of seismic activity reminiscent of the activity prior to a previous major eruption in the area.

  • UPFLOW Ocean-bottom Seismometer deployment, Atlantic Ocean

    • 2-month expedition at sea deploying ocean-bottom seismometers to study upwellings of mantle material beneath the Azores archipelago. Part of the H2020 ERC Consolidator Grant UPFLOW (101001601).

  • GeoTenerife Magnetotelluric survey of Gran Canaria, Spain

    • Deployment of magnetotelluric instruments on Gran Canaria in the search for geothermal resources.

Volunteering Activities and Service

  • External Examiner, University of Durham MScR in Geological Science (2025)

  • RSES Education Committee ECR Representative (2024)

  • Journal Peer-Reviewing

    • Geophysical Journal International (2022, 2024)

    • Journal of Geophysical Research: Solid Earth (2022)

    • Physics of the Earth and Planetary Interiors (2021, 2023)

  • Expert Examiner RSES Masters of Earth Sciences (Advanced)

    • Jiarun Zhou (2023). Developing a deep-learning model to detect and measure the Earth’s inner-core sensitive waves. Supervised by Prof. Hrvoje Tkalčić and Dr Thanh-Son Phạm.

  • Session Convener

    • Kennett Symposium (2023), Canberra

    • ANU RSES Geophysics Weekly Meeting (08/2023–12/2023)

Outreach and Communication Activities

  • UCL GeoBus Earthquake Simulation, ACS STEAM Fair, London

  • UPFLOW Outreach and Communications Team and Web Designer

Publications

[1] A. Marignier, C. M. Eakin, and M. S. Miller, “Sediment thickness of the contiguous united states from teleseismic receiver functions,” Seismological Research Letters, Jun. 2025, doi: 10.1785/0220250077. Available: https://doi.org/10.1785/0220250077

[2] A. Marignier, C. M. Eakin, B. Hejrani, S. Agrawal, and R. Hassan, “Sediment thickness across Australia from passive seismic methods,” Geophysical Journal International, vol. 237, no. 2, pp. 849–861, May 2024, doi: 10.1093/gji/ggae070. Available: https://doi.org/10.1093/gji/ggae070. [Accessed: May 20, 2024]

[3] A. Marignier, J. D. McEwen, A. M. G. Ferreira, and T. D. Kitching, “Posterior sampling for inverse imaging problems on the sphere in seismology and cosmology,” RAS Techniques and Instruments, vol. 2, no. 1, pp. 20–32, 2023, doi: 10.1093/rasti/rzac010. Available: https://doi.org/10.1093/rasti/rzac010. [Accessed: Jun. 11, 2024]

[4] A. Marignier, T. D. Kitching, J. D. McEwen, and A. M. G. Ferreira, “Sparse Bayesian mass-mapping using trans-dimensional MCMC,” The Open Journal of Astrophysics, vol. 6, 2023, doi: 10.21105/astro.2211.13963. Available: https://doi.org/10.21105/astro.2211.13963. [Accessed: Jun. 11, 2024]

[5] A. Marignier, “PxMCMC: A Python package for proximal Markov Chain Monte Carlo,” Journal of Open Source Software, vol. 8, no. 87, p. 5582, 2023, doi: 10.21105/joss.05582. Available: https://doi.org/10.21105/joss.05582. [Accessed: Jun. 11, 2024]

[6] A. Marignier, “From Dark Matter to the Earth’s Deep Interior: There and Back Again,” PhD thesis, University College London, 2023. Available: https://discovery.ucl.ac.uk/id/eprint/10162902

[7] M. A. Price, M. Mars, M. M. Docherty, A. S. Mancini, A. Marignier, and J. D. McEwen, “Fast emulation of anisotropies induced in the cosmic microwave background by cosmic strings,” The Open Journal of Astrophysics, vol. 6, 2023, doi: 10.21105/astro.2307.04798. Available: https://doi.org/10.21105/astro.2307.04798. [Accessed: Jun. 11, 2024]

[8] W. Sturgeon, A. M. G. Ferreira, L. Schardong, and A. Marignier, “Crustal Structure of the Western U.S. From Rayleigh and Love Wave Amplification Data,” Journal of Geophysical Research: Solid Earth, vol. 128, no. 8, p. e2022JB026148, 2023, doi: 10.1029/2022JB026148. Available: https://doi.org/10.1029/2022JB026148. [Accessed: May 26, 2024]

[9] O. J. Cobb et al., “Efficient Generalized Spherical CNNs,” in International conference on learning representations, 2021. Available: https://arxiv.org/abs/2010.11661v3. [Accessed: Jun. 11, 2024]

[10] A. M. G. Ferreira, A. Marignier, J. Attanayake, M. Frietsch, and A. Berbellini, “Crustal structure of the Azores Archipelago from Rayleigh wave ellipticity data,” Geophysical Journal International, vol. 221, no. 2, pp. 1232–1247, May 2020, doi: 10.1093/gji/ggaa076. Available: https://doi.org/10.1093/gji/ggaa076. [Accessed: Jun. 11, 2024]

[11] A. Marignier, A. M. G. Ferreira, and T. D. Kitching, “The Probability of Mantle Plumes in Global Tomographic Models,” Geochemistry, Geophysics, Geosystems, vol. 21, no. 9, p. e2020GC009276, 2020, doi: 10.1029/2020GC009276. Available: https://doi.org/10.1029/2020GC009276. [Accessed: Jun. 11, 2024]

[12] J. He, M. Sambridge, J. Hauser, A. P. Valentine, F. Magrini, and A. Marignier, “CoFI: Linking geoscience inference problems with tools for their solution.”

[13] S. P. Hicks et al., “Leaky faults modulated magma ascent and adjacent seismicity during the 2022 São Jorge Island (Azores) seismic-volcanic unrest.” Available: https://eartharxiv.org/repository/view/8224/

[14] A. Marignier, J. Hauser, and M. Sambridge, “Opinionated inversion and regularisation approaches for delineation of DCIP targets.”

[15] M. Tsekhmistrenko et al., “Performance of the 2021-2022 UPFLOW large ocean bottom seismometer array in the Azores-Madeira-Canary Islands region, Atlantic Ocean.”