Welcome
Last updated: 24 September 2025
About me
Hello, my name is Yuke, I am a final (3rd) year PhD candidate in ML & Geophysics at Mines Paris-PSL, and I am also a member of the Horizon 2020-Marie Skłodowska-Curie Actions-COFUND European program AI4theSciences at PSL University. I’m the parent of a British Shorthair🐱 and I love sports.
Education
- PhD student in Geophysics
Oct 2022 - Present
Mines Paris-PSL, Fontainebleau, France- Inverse problem, stochastic full waveform inversion, deep generative models, variational Bayesian inference
- European Marie Curie PhD fellow, Horizon 2020 MSCA-PSL Cofund Program AI4theSciences
- Research Internship
Feb 2022 - Aug 2022
CNRS, Dauphine-PSL, Paris, France- Internship at LAMSADE UMR CNRS Research Center
- Master of Engineering, GeoEngine
2019 - 2022
University of Stuttgart, Stuttgart, Germany- Best master thesis (MSc. Preisträger 2023) award F2GeoS of year 2023
- Masterarbeit: Ship-based GNSS ionospheric observations for the detection of tsunami
- Student Assistant (Aug 2020 - Nov 2021)
- Bachelor of Engineering, Geodesy
2015 - 2019
Wuhan University, Wuhan, China
Interests
- Deep Learning, Inverse problem, Deep generative models, Machine learning statistics
- Geophysics, Geostatistics, Geoinformatics
- Earth Observation, GNSS
- Sports
Research items
Xie, Y., Chauris, H., & Desassis, N. (2025). Diffusion prior as a direct regularization term for FWI. arXiv preprint arXiv:2506.10141.
Xie, Y., Chauris, H., & Desassis, N. (2025). Generative AI Prior and Posterior Sampling for Seismic Imaging. 86th EAGE Annual Conference & Exhibition (Conference Proceedings). doi: 10.3997/2214-4609.202510982
Xie, Y., Chauris, H., & Desassis, N. (2024). Bayesian posterior sampling in non-linear seismic inverse problem using deep generative prior. AGU Fall Meeting 2024 Poster. doi: 10.22541/essoar.173655494.46692293
Xie, Y., Chauris, H., & Desassis, N. (2024). Stochastic full waveform inversion with deep generative prior for uncertainty quantification. arXiv preprint arXiv:2406.04859.
Xie, Y., Chauris, H., & Desassis, N. (2024). Deep Generative Models for Stochastic Seismic Imaging and Uncertainty Quantification. 85th EAGE Annual Conference & Exhibition. doi: 10.3997/2214-4609.202410495
Foster, J., Ericksen, T., Thomas, B., Avery, J., Xie, Y., & Knogl, R. (2024). Augmenting Tsunami Detection with a Ship-based GNSS Network. EGU General Assembly 2024. doi: 10.5194/egusphere-egu24-5841
Kougkoulos, I., Xie, Y., Merad, M., & Cook, S. J. (2023). Choosing the appropriate spatial scale for flash flood risk assessments in Mediterranean mountain watersheds. EGU General Assembly 2023. doi: 10.5194/egusphere-egu23-4320
Xie, Y., Foster, J., Ravanelli, M., & Crespi, M. (2022). Ship-based GNSS ionospheric observations for the detection of tsunamis with deep learning. EGU General Assembly 2022. doi: 10.5194/egusphere-egu22-405
Talks
[Poster] Bayesian posterior sampling in non-linear seismic inverse problem using deep generative prior, Doctoral Conference AI for The Sciences, 23 May 2025, Mines Paris - PSL, Paris, France
[Invited talk] Generative priors and uncertainty quantification in seismic imaging, EAGE Local Chapter Paris Webinar, 15 May 2025, Paris, France
[Poster (PDF)] Uncertainty quantification in computational inverse problem using deep generative models, Deep Learning for Science Day (JDLS), French National Centre for Scientific Research (CNRS), May 2024, Paris, France
[Presentation (PDF)] Deep Generative Models for Stochastic Geophysical Imaging and Uncertainty Quantification, Generative models in artificial intelligence: Theory, learning and environmental applications, RESSTE network, 22 May 2024, Paris, France
[Abstract (PDF)] Posterior sampling methods using Bayesian deep generative prior, Doctoral Conference AI for The Sciences, Paris Dauphine University, 15 May 2024 - 16 May 2024, Paris, France
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