Project description
Using AI to model structural earth risks beneath cities
Beneath our feet lies a network of fault lines and fragile sedimentary basins that threaten major cities. While monitoring networks capture massive seismic data from these hazards, our ability to interpret it is limited. Computer models are too slow to process these large datasets, causing scientists to miss small-scale underground shifts that signal impending disasters. Supported by the Marie Skłodowska-Curie Actions programme, the NEURO-TOMO project will introduce a new computational approach to tackle this problem. Researchers will leverage AI to simulate how seismic waves travel through different materials. They will analyse dense geological data worldwide, including major volcanic networks. Ultimately, the AI will scan standard fibre-optic cables beneath cities, transforming existing urban infrastructure into vast, highly accurate seismic detectors.
Objective
Understanding the fine structure of the Earth is critical for mitigating earthquake risk, assessing volcanic activity, and ensuring the stability of sedimentary basins beneath major cities. Current seismic imaging methods can map subsurface structures, but they face major computational challenges with large datasets. Calculations are slow and often miss small-scale features that are crucial for hazard assessment, limiting our ability to exploit the growing volume of seismic data worldwide.
Recent advances in artificial intelligence offer a pathway to overcome these barriers. Machine learning can capture the relationship between Earth structure and seismic wave propagation, enabling accurate waves simulations orders of magnitude faster than traditional methods. This makes it possible to explore thousands of Earth models and quantify uncertainty in imaging results, providing confidence levels that were previously too costly to compute.
In this project, I will advance AI-based techniques for seismic imaging and apply them to dense datasets at multiple scales. A key target is the MACIV experiment, the largest volcanological deployment to date, with 150 broadband and 600 short-period stations, offering a unique chance to probe intraplate volcanic systems in Europe. I will also test the framework on other networks, including USArray and AlpArray to apply it across diverse geological context.
I will then extend these advances to Distributed Acoustic Sensing (DAS), which converts existing fibre-optic cables into seismic arrays. This step requires further development to handle the variable quality and geometry of DAS data. By adapting the workflow to both dense arrays and DAS, the project will deliver a robust framework for seismic imaging that is transferable across environments from volcanoes to urban basins at different scales, demonstrating how cutting-edge AI can unlock new value from the massive seismic datasets already being collected worldwide.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences earth and related environmental sciences geology volcanology
- natural sciences earth and related environmental sciences geology seismology
- natural sciences mathematics pure mathematics geometry
You need to log in or register to use this function
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
-
HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
See all projects funded under this programme
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-GF - HORIZON TMA MSCA Postdoctoral Fellowships - Global Fellowships
See all projects funded under this funding scheme
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
See all projects funded under this callCoordinator
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
8092 Zuerich
Switzerland
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.