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P32 - InterTwin - An Interdisciplinary Digital Twin Engine for Science

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CEST
Climate, Weather and Earth Sciences
Chemistry and Materials
Computer Science, Machine Learning, and Applied Mathematics
Applied Social Sciences and Humanities
Engineering
Life Sciences
Physics
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Description

The interTwin project, funded by the European Commission, is at the forefront of leveraging 'Digital Twins' across various scientific domains, with a particular emphasis on earth observation and physics. This initiative encompasses core modules designed to address the intricacies of data-driven and compute-intensive applications. From real-time data acquisition, software quality and Artificial Intelligence (AI), interTwin aims to facilitate seamless communication and interoperability across High Performance Computing (HPC), High Throughput Computing (HTC), and cloud resources for the benefit of physics and earth observation research.

Presenter(s)

Presenter

Matteo
Bunino
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CERN

Matteo Bunino earned a double MSc degree in Data Science and Computer Engineering from the Polytechnic University of Turin (Italy) and EURECOM (France). He worked at Huawei's Munich Research Center (MRC) on AI-powered malware analysis, resorting to reinforcement learning, NLP, and graph machine learning.Currently, Matteo is a fellow in the IT department at CERN and he is working on interTwin, a European project aimed at developing a unified digital twin engine (DTE) for science. In particular, Matteo is the main developer of "itwinai", a toolkit for advanced MLOps on cloud and HPC aimed at simplifying the access to large-scale distributed ML and hyper-parameter optimization for scientific use cases. Moreover, Matteo is also part of CERN openlab, where he is investigating digital twin applications with Nvidia Omniverse and heterogeneous computing benchmarking.

Authors