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Real-time inversion using self-explainable deep learning driven by expert knowledge
Real-time inversion using self-explainable deep learning driven by expert knowledge
IN-DEEP is a European Doctoral Network composed of nine doctoral candidates (DCs) and top scientists with complementary areas of expertise in applied mathematics, artificial intelligence, high-performance computing, and engineering applications. Its main goal is to provide high-level training to the nine DCs in designing, implementing, and using explainable knowledge-driven Deep Learning algorithms for rapidly and accurately solving inverse problems governed by PDEs. This area of research has experienced tremendous growth worldwide in the last lustrum due to its promising results in a plethora of applications, such as image recognition and natural language processing. IN-DEEP will focus on real-life high-risk problems arising from applications related to geophysics, smart cities, and health. By doing so, we will boost Europe’s training and research activities in new Deep Learning technologies for inverse problems.
IN-DEEP will develop fundamental research at universities and research institutes that will be validated and applied to real-world use cases in technology centers and companies.
Dates
Dates
Feb 1st, 2024 - Jan 31st, 2028
Beneficiaries
Beneficiaries
Associated Partners
Associated Partners
Management
Management
Project Management Team: David Pardo (Project Coordinator, UPV/EHU), Izaskun Ibarbia (Administrative Coordinator, UPV/EHU), Magdalena Strugaru (Project Manager, UPV/EHU)
Innovation Manager: Nerea Mena (BCAM)
Ethics Manager: Francisco Chinesta (ENSAM)
Scientific Committee: David Pardo (UPV/EHU), Alessandro Reali (UniPV), Judit Muñoz-Matute (BCAM), Maciej Paszynski (AGH), Kristopher Van der Zee (UoN), Stefano Berrone (POLITO), Javier Del Ser (Tecnalia), Gwendal Jouan (Siemens), and Francisco Chinesta (ENSAM)
Supervisory Board: David Pardo (UPV/EHU), Alessandro Reali (UniPV), Judit Muñoz-Matute (BCAM), Maciej Paszynski (AGH), Kristopher Van der Zee (UoN), Stefano Berrone (POLITO), Javier Del Ser (Tecnalia), Gwendal Jouan (Siemens), Francisco Chinesta (ENSAM), Ivan Bioli (DC representative, UniPV)
OTHER INFO
OTHER INFO
Newsletters & Leaflets
Newsletters & Leaflets
Links
Links
IN-DEEP VALUES: ONE PERSON, ONE VALUE
IN-DEEP VALUES: ONE PERSON, ONE VALUE
IN-DEEP members whose main motivations are health and sexual orientation, among others, share their stories and challenges. This action encourages the DCs, other researchers, and the general public to embrace their uniqueness and difference from others, and thus to activate their natural motivation, which will lead them not just to survive, but to thrive.
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