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CORDIS

Confident data-driven Decision Support

Project description

Smarter Decisions, Powered by Responsible AI

Reducing emissions, managing limited resources, and other modern challenges demand smarter, faster decisions. Supported by the Marie Skłodowska-Curie Actions programme, the CoRDS project is building the next generation of AI-powered tools to support complex decision-making across sectors like logistics, healthcare, and finance. By fusing Operations Research with Machine Learning, CoRDS pioneers data-driven optimisation tools that empower decision makers to find high-quality solutions to complex challenges. These tools will be designed to ensure transparency, safety, and fairness. At the heart of the project is a new doctoral training network, equipping researchers to turn cutting-edge theory into practical tools. CoRDS will also create a lasting framework to train future experts who can shape the fast-evolving landscape of AI-driven decision-making.

Objective

The CoRDS project addresses building the next generation of artificial intelligence (AI)-powered decision support tools to allow organizations to tackle complex decision-making problems more effectively and responsibly,  such as efficiently managing scarce (natural) resources and reducing their carbon footprints. These tools unify two areas of research, namely Operations Research (OR) and Machine Learning (ML). In OR, specialized optimization methods have been developed to address complex decision problems, but these rely heavily on expert knowledge, limiting their ability to adapt to changing data. Conversely, ML excels in leveraging extensive data for predictive tasks, but struggles with combinatorial optimization. Integrating OR and ML, leading to data-driven optimization (DDO) tools, presents a promising avenue to enhance decision support by combining OR's problem-solving capabilities with ML's data utilization strengths. Furthermore, DDO tools must not only provide high-quality decisions to users in low computational time, they must also comply with government and industry standards, and therefore must be safe, transparent, traceable and non-discriminatory, i.e. follow the principles of trustworthy AI, a significant challenge for most current AI systems. The expertise needed to create and apply DDO methods to real-world problems is severely lacking. The CoRDS doctoral network addresses this critical need by developing a training program to sculpt the next generation of analytics experts combining OR and ML, who will translate their research into prototype tools to address real-life problems defined in collaboration with our industrial partners across various application sectors, including logistics, healthcare, public transportation, production, finance, publishing and machine translation. The CoRDS network further delivers a training framework for others to use and expand.

Keywords

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Programme(s)

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Topic(s)

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Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

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-2024-DN-01

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Coordinator

UNIVERSITAET BIELEFELD
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.

€ 580 544,64
Address
UNIVERSITAETSSTRASSE 25
33615 BIELEFELD
Germany

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Region
Nordrhein-Westfalen Detmold Bielefeld, Kreisfreie Stadt
Activity type
Higher or Secondary Education Establishments
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Total cost

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Participants (8)

Partners (13)

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