| Project Detail |
Research collaboration for data-driven large-scale decision-making
As innovative AI technologies advance, dynamic decision-making becomes increasingly crucial in the ever-expanding Internet of Things (IoT) landscape. However, making dynamic decisions in large-scale uncertain systems poses challenges in modern data-rich operational environments. Traditional decision support systems are becoming obsolete in these settings, making it difficult to ensure fairness and transparency. The EU-funded TwinODIS project aims to revolutionise data-driven large-scale decision optimisation using AI technology and operational research analytical methods. The project will bring together specialists in computer science and large-scale decision intelligence from Dutch, French, and Greek research institutions. Through collaboration, extensive knowledge transfer, and training, the project seeks to advance the field.
Dynamic decision-making in large-scale uncertain systems poses significant challenges in modern data-rich operational environments. Traditional decision support systems struggle to manage vast and complex datasets in real time, while handling multiple conflicting objectives of high-dimensional problems and ensuring fairness and transparency in decision-making. A fundamentally new perspective is necessary to address these challenges by adopting a holistic, cross-disciplinary approach that bridges the realms of Artificial Intelligence (AI) and Operations Research (OR). This approach will pave the way for the next-generation Decision Intelligence systems, driving sustainable development and economic growth.
TwinODIS is a transformative project aimed to revolutionize data-driven large-scale decision optimization through the integration of AI technologies and OR analytical methods. A group of excellence will be established in the emerging field of Large-Scale Decision Intelligence, by twinning the Institute of Computer Science at the Foundation for Research & Technology-Hellas (FORTH, Greece) with two internationally-leading research institutions, namely, the Laboratory of Informatics Paris Descartes, Université Paris Cité (UPC, France) and the Erasmus School of Economics, Erasmus University Rotterdam (EUR, Netherlands). The project leverages comprehensive knowledge transfer, training and networking programmes to elevate FORTHs scientific profile and research capacity, foster an innovation culture to attract industrial investments, engage in competitive EU projects, and enrich the skills of senior scientists in administrative and management aspects, positioning FORTH as a prominent AI-driven Decision Science Hub in Greece and South-Eastern Europe. |
