Developing the grey-box
methodology
GREYDIENT advances the state of the art for grey-box approaches for multi-fidelity modelling, reliability analysis and uncertainty quantification to enable the widest possible application in engineering and far beyond. GREYDIENT GREYDIENT advances the state of the art for grey-box approaches for multi-fidelity modelling, reliability analysis and uncertainty quantification to enable the widest possible application in engineering and far beyond.
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Developing the grey-box
methodology
GREYDIENT Designing vehicles that
are reliable and safe
GREYDIENT is about innovation in the automotive sector, but with developments being applicable to a broader product-design context that makes use of numerical simulations. GREYDIENT GREYDIENT is about innovation in the automotive sector, but with developments being applicable to a broader product-design context that makes use of numerical simulations.
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Designing vehicles that
are reliable and safe
GREYDIENT Continuous monitoring,
optimization and control GREYDIENT develops grey-box methods for the monitoring, optimization and control of complex processes and systems, such as manufacturing processes and/or energy grids, paving the way for fully intelligent networks and infrastructural systems. GREYDIENT GREYDIENT develops grey-box methods for the monitoring, optimization and control of complex processes and systems, such as manufacturing processes and/or energy grids, paving the way for fully intelligent networks and infrastructural systems.
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Continuous monitoring,
optimization and control GREYDIENT
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We are hiring...

We are looking for entusiastic and highly motivated Early Stage Researchers (ESR) to join our team to develop grey-box modelling approaches to shape the future of intelligent mobility systems. [Applications deadline: 31/03/2021]

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Greydient

"With GREYDIENT, we want to push the state of the art in grey-box modelling. Whereas so far, endeavours to improve the reliability and robustness of components, processes and systems have focused on using either data-driven black-box methods or first-principle white-box techniques, we believe the future lies in their optimal combination: grey-boxes."

KU LEUVEN

Dr. Matthias Faes

"For a sustainable World, we have the honest duty of designing and operating systems and infrastructures in a way that they are reliable and safe. Our World is a VUCA World-Vulnerable, Uncertain, Complex and Ambiguous. Then, the solutions to our problems cannot be black or white: they must be inevitably grey. In this project, we aim at advancing, with a big leap, the grey-box modeling capability for uncertainty quantification (UQ) and reliability assessment (RA), to the benefit of reliable and safe design and operation of systems and infrastructures."

POLITECNICO DI MILANO

Prof. Dr. Enrico Zio

"GREYDIENT is a unique opportunity for us to engage in this emerging field at the boundary of machine learning for data science and scientific computing for uncertainty quantification. The Consortium led by KU Leuven gathers both top European academic institutions in the field of uncertainty quantification and reliability of systems and major tech companies. This will allow us to develop new solutions that are truly applicable by the automotive and aerospace industry."

ETH Zürich

Prof. Dr. Bruno SUDRET

Greydient Consortium

Greydient brings together experts from academy and leading European companies: 6 countries, 7 universities and 11 industrial partners.