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"A Europe for the digital age" and "The European Green Deal" are two of six political priorities defined by the European Commission to address the grand challenges to be faced by the EU and its citizens. Both priorities are mutually dependent, and solutions developed for addressing them can ideally reinforce each other. For example, digital twins, virtual copies of the real world, are able to model various processes (from traffic to manufacturing) and optimise them in such a way that emissions are reduced and resources are saved. On the other hand, energy-efficient High Performance Computing solutions can give a boost to research in the field of Artificial Intelligence (AI).
The huge recent advances in Machine Learning (ML) and Deep Learning algorithms have the potential to revolutionise the decision-making processes across all sectors of society, including manufacturing, healthcare and the life sciences, energy and the environment, transportation, and smart cities. However, the widespread adoption of such techniques is still hindered by the perceived untrustworthiness of their outputs. The High-Level Expert Group on AI set up by the European Commission identifies trustworthy Artificial Intelligence as their primary focus. Even more so in the metrological context, it is essential that predictions based upon ML are quality assured and traceable to reference standards.
European Network for Mathematics and Statistics in Metrology
In this complex framework, EURAMET has founded the European Network for Mathematics and Statistics in Metrology (EMN Mathmet) as a central reference point to tackle the mathematical, modelling, computational and statistical aspects of challenges such as those outlined above. The EMN addresses the need for integration between measurement science and mathematical and statistical methods and aims at fostering the field of mathematical and statistical applications for measurement science in Europe.
EMN Mathmet Strategic Research Agenda
Based on an extensive consultation process with its stakeholders and the strategies of individual NMIs and DIs, and in alignment with the EURAMET 2030 strategy, the EMN has developed a Strategic Research Agenda (SRA) that will serve as an essential reference point to guide the network’s collaborative metrological research activities.
In the document, the emerging research topics of:
- Artificial Intelligence and Machine Learning, and
- Computational Modelling and Virtual Metrology have been incorporated and linked to the more traditional area of
- Data Analysis and Uncertainty Evaluation.
The SRA characterises the future needs and challenges in the field of mathematics and statistics in metrology and provides an outline of how the EMN Mathmet can meet these new emerging requirements.
Francesca Pennecchi, Chair of the EMN, comments:
“In its draft version, the Mathmet SRA has already made good impact, providing input to the strategy of some National Measurement Institutes on Artificial Intelligence, and to several EURAMET Potential Research Topics and Joint Research Projects. It was also provided as an input to a questionnaire on the CIPM Strategy 2030+. Now that it is published in its final version, it is expected to serve as a reference document for guiding Mathmet Members’ research efforts and enabling their interaction with high-level stakeholders and other Partnerships, as well as to influence future European Partnership on Metrology calls and collaborative research projects in the field of maths and stats for metrology.”
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