SUSTAIN (SUbstrate and Systems of Trays for Agricultural INnovation) is a five-year project funded under the Italian Applied Sciences Fund (FISA 2024) programme of the
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Author: nicoparo
MOX. Decoding Brain Function through Mathematical Modeling, Scientific Computing & Computational Learning (BrainNum)
BraiNum is a research project carried out at the MOX Laboratory (Department of Mathematics, Politecnico di Milano) devoted to the mathematical modeling and numerical simulation
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MOX. Digital twin for rock fall and flow in response to a climate change scenario (TWINFALL)
TWINFALL “Digital TWIN for rock FALL and flow in response to a climate change scenario” is a project carried out in collaboration between the Department
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MOX. ICOSAHOM 2027 at Politecnico di Milano (Italy) from 5–9 July 2027
We are proud to announce that ICOSAHOM 2027 – the 16th International Conference on Spectral and High-Order Methods will be held at Politecnico di Milano
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Milano. Digital twins in orbit
In satellite space missions, the ability to extract information from sensor data is crucial to monitor the operational status of the satellite, to predict future
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MULTISCALE MODELS IN ACTION
Geometrical multiscale models have been subject of investigation by MOX researcher since many years. Today, the focus is on multiscale problems characterized by the strong
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Modelling fault reactivation
Researchers in the Computational Geosciences group at the MOX Laboratory (https://mox.polimi.it/) have been working for the last 6 years on the problem of induced seismicity
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Mathematics at the service of the heart
iHEART, that is “an integrated heart model for the simulation of the cardiac function”, is an attempt to create a complete mathematical model of the
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A space adventure for MOX
The MOX Laboratory (https://mox.polimi.it/) is participating in a Joint Programme between Politecnico di Milano and ASI (Italian Space Agency) (www.asi.it) covering different aspects of space
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Object-Oriented Spatial Statistics for the geosciences
The advent of modern technologies for data acquisition is leading to data-rich industrial and environmental contexts. Not only large datasets, but most often complex types
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