Research Area: My main work currently focuses on computational methods for large scale inverse problems such as seismic inversion. Inverse problems such as seismic inversion require access to scientific computing framework in order to solve the wave equation. With Devito, my main work during my Ph.D, I provide a high-level symbolic DSL for the definition of partial differential equation. Devito then automatically generate and compile highly performant low-level C-code to solve the wave--equation while domain specialist such as geophysicist or mathematics only need to define it at a readable level. This works enable research and development that would be unfeasible or would requires years of work without the simple and accessible interface and solver I developed. I am also working on methods for solving seismic inversion problems, that are non-convex PDE constrained optimization problems, as well as on the extension to advanced representations of the physics of methods that are currently restricted to the trivial isotropic acoustic case.
Devito is an open-source project that can be found at:
https://www.devitoproject.org
https://github.com/opesci/devito
Homepage: https://github.com/mloubout
About me: Ph.D. student at Georgia Institute of Technology, School of computing, CSE. I completed a Bs.C. in Mathematics and Physics, did two years of aircraft engineering and obtained a Ms.C in applied Mathematics with honors at Universite of Rennes 1 in France before starting my Ph.D. with Professor Felix. J. Herrmann. Expected to graduate in Spring 2020.
Homepage: https://github.com/mloubout
About me: Ph.D. student at Georgia Institute of Technology, School of computing, CSE. I completed a Bs.C. in Mathematics and Physics, did two years of aircraft engineering and obtained a Ms.C in applied Mathematics with honors at Universite of Rennes 1 in France before starting my Ph.D. with Professor Felix. J. Herrmann. Expected to graduate in Spring 2020.
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, “Digital Twins in the Era of Generative AI: Application to Geological CO 2 Storage”, HCMF Seminar. 2024.
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, “Generative AI for full-waveform variational inference”, Georgia Tech Geophysics Seminar. 2024.
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, “WISE: full-Waveform variational Inference via Subsurface Extensions”, Geophysics, 2024.
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, “Normalizing Flows for Bayesian Experimental Design in Imaging Applications”, in SIAM Conference on Uncertainty Quantification, 2024.
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, “An Uncertainty-Aware Digital Twin for Geological Carbon Storage”, in SIAM Conference on Uncertainty Quantification, 2024.
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, “Uncertainty quantification so what? Leveraging probabilistic seismic inversion for experimental design”, ML4SEISMIC Partners Meeting. 2023.
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, “Towards generative seismic kriging with normalizing flows”, ML4SEISMIC Partners Meeting. 2023.
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, “Time-lapse seismic monitoring of geological carbon storage with the nonlinear joint recovery model”, ML4SEISMIC Partners Meeting. 2023.
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, “Solving PDE-based inverse problems with learned surrogates and constraints”, HotCSE Seminar. 2023.
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, “Monitoring subsurface CO2 plumes with learned sequential Bayesian inference”, ML4SEISMIC Partners Meeting. 2023.
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, “WISE: Full-waveform Inference with Subsurface Extensions”, ML4SEISMIC Partners Meeting. 2023.
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, “Improved automatic seismic CO2 leakage detection via dataset augmentation”, ML4SEISMIC Partners Meeting. 2023.
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, “End-to-end permeability inversion from prestack time-lapse seismic data: a case study on Compass model”, ML4SEISMIC Partners Meeting. 2023.
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, “Solving multiphysics-based inverse problems with learned surrogates and constraints”, Advanced Modeling and Simulation in Engineering Sciences, vol. 10, 2023.
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, “Enhancing CO2 Leakage Detectability via Dataset Augmentation”, in International Meeting for Applied Geoscience and Energy, 2023.
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, “Learned non-linear simultenous source and corresponding supershot for seismic imaging.”, in International Meeting for Applied Geoscience and Energy, 2023.
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, “Fast neural FWI with amortized uncertainty quantification”, in International Meeting for Applied Geoscience and Energy, 2023.