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 of data, such as curves, images or tensors, are routinely collected in data-driven engineering applications, posing new challenges for geo-scientists. In recent years, the Statistics […]

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Functional and Object-oriented Data Analysis for Mobility

Statisticians are currently asked to develop tools to analyze extremely complex data often far from the standard Euclidean framework (e.g., curves, networks, compositions, images, tensors). The Statistics group at MOX proposes a paradigm of statistical investigation based on the idea of developing sound approaches to data analysis able to provide […]

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ESCAPE-2: a Future and Emerging Technologies HPC project

MOX researchers Luca Bonaventura and Tommaso Benacchio are involved in the H2020, Future and Emerging Technologies HPC project ESCAPE-2. This project will develop world-class, extreme-scale computing capabilities for European operational numerical weather and climate prediction systems. It continues the pioneering work of the ESCAPE project. The project aims to attack […]

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Simpaty: topology optimization for free-form design

Professors Simona Perotto and Stefano Micheletti, in collaboration with Thales Alenia Space Italia, at MOX Laboratory of Politecnico di Milano have developed a new mathematical algorithm, named Simpaty, that can be employed in a finite element setting for the topology optimization of mechanical components. The resulting configurations are characterized by […]

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Reduced models for the packaging industry

Model reduction techniques based on either geometrical multi-scale modeling (coupling of differential models operating at different spatial dimensions) or reduced order modeling (e.g. Proper Orthogonal Decomposition or Reduced Basis) have proved very successful for the simulation of complex integrated systems, such as the human cardiovascular system. The long-lasting experience at […]

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Statistical Analysis of High Dimensional & Complex Data

The last years have seen the advent and development of many devices able to record and store an always increasing amount of complex and high dimensional data: 3D images generated by medical scanners, satellite remote sensing, system control datasets, administrative databases, mobile phone data, etc. The analysis of these complex […]

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Physics-based numerical modeling for seismic risk mitigation

Mathematical and numerical modeling can be used to better understand the physics of earthquakes, improve the design of site-specific structures and facilities, and enhance seismic risk maps. The reliability of existing tools for earthquake and ground-motion prediction, i.e. Ground Motion Prediction Equations (GMPEs), which are based on empirical relations involving […]

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Computational Geomechanics at MOX

The CompGeo group of the MOX Laboratory gathers researchers in numerical analysis and statistics with the purpose of studying the complex coupled problems related to flow and deformation in the subsurface at different time and space scales, with a focus on energy and risk assessment. Fault reactivation We are investigating […]

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An Integrated Heart Model for the simulation of the cardiac function

iHEART – “An Integrated Heart Model for the simulation of the cardiac function” (2017-2022) is a ERC Advanced Grant awarded to Prof. Alfio Quarteroni in the framework of the “H2020 – Excellent Science – European Research Council” program. Mathematician Alfio Quarteroni and his research team at MOX-Politecnico di Milano (Italy) […]

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