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Challenging AI with Challenges from Physics: How to solve fundamental problems in Physics by AI and vice versa

Project description

Europe’s strategic response to AI innovation in particle physics

In the rapidly evolving landscape of AI technology, European industry and research face formidable challenges from global competitors. The AIPHY project emerges as a pioneering initiative to integrate advanced AI concepts with practical applications, particularly in the complex realm of particle physics. With the support of the Marie Skłodowska-Curie Actions (MSCA) programme, it has formed a consortium of nine distinguished researchers across physics and computer science from five European universities. The project’s aim is to address critical issues like solving ill-posed inverse problems, handling uncertainties in data, and providing transparent machine learning insights based on physics principles. Overall, AIPHY will push the boundaries of AI research and prepare future leaders with essential skills for academia and industry.

Objective

AI is a disruptive technology that is currently changing not only many research fields but also substantially challenges current business concepts. Keeping up with the ever-faster progress on one hand side and the ever increasing competition from US and Chinese IT giants is a challenge for European Industry and Research Institutions. Yet, new concepts are required to keep pace. This concept is to intertwine modern AI concepts with strategies from the application field, a strategy where we claim that we can contribute substantially to a novel and promising research field.

Particle physics is a formidable basis for such developments as there are no critical, personal data, data can be easily generated; and we have a good understanding of the underlying models and the ground truth. Yet, particle physics has challenges such as detailed questions of new physics and extremely high precision of the results. We identified three main fields where this project will contribute by solving 1) highly ill-posed inverse problems using physics models, 2) handling uncertainties, rare events and give reliable error bounds, and finally, 3) to be able to give explanations of the machine learning results in terms of physics ontologies and models.

This highly challenging research agenda is tackled by 9 internationally recognized and leading researchers from both physics and computer science, from 5 universities in 5 European countries, all being member of the 4EU+ Alliance of European Universities. Over 4EU+ an excellent infrastructure for unique training opportunities is available to enable the research fellows to reach the ambitious goals, on one hand side and to educate them in critical and innovative thinking, management and social skills to prepare them optimally for leading positions in academics and industry.

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Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

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HORIZON-TMA-MSCA-DN - HORIZON TMA MSCA Doctoral Networks

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Call for proposal

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(opens in new window) HORIZON-MSCA-2023-DN-01

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Coordinator

RUPRECHT-KARLS-UNIVERSITAET HEIDELBERG
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 521 078,40
Address
SEMINARSTRASSE 2
69117 Heidelberg
Germany

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Region
Baden-Württemberg Karlsruhe Heidelberg, Stadtkreis
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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Participants (4)

Partners (5)

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