Explainable AI – Multimodal Data Fusion and Analytics Group

DISARM

DISARM Disarming the silent threat of ovarian cancer Ovarian cancer (OC), a malignant tumour in one or both ovaries, is the most lethal of female gynecologic cancers in Europe. Often referred to as a “silent killer,” OC is typically diagnosed at an advanced stage due to its subtle, non-specific symptoms, and the lack of effective screening, underscoring the urgent need for improved early detection strategies. As one of the most heritable forms of cancer, with a significant proportion of cases linked to family history and genetic predisposition, OC also highlights the critical importance of multifactorial risk assessment tools to accurately identify high-risk individuals and enable targeted prevention. The DISARM project addresses these critical challenges of hereditary OC by advancing both multifactorial risk assessment and early detection through cutting-edge technologies. By…

MaaSAI

MaaSAI MaaSAI | Agile Manufacturing as a Service through AI Autonomous Agents The goal of the project is the creation of the MaaSAI System, a comprehensive digital system to automate and facilitate interactions between suppliers of manufacturing systems (Providers) and manufacturing companies (Consumers) in a Manufacturing-as-a-Service (MaaS) ecosystem, in an agile, efficient, and transparent manner. The MaaSAI System aims to revolutionise manufacturing and remanufacturing processes by facilitating access to flexible and decentralised capacities, through the MaaS business model, which extends the principles of the service-oriented economy to the manufacturing industry. The MaaSAI System aims to contribute to the reduction of the heavy investments that manufacturers have traditionally had to make to set up and maintain their operations. With an emphasis on production flexibility, agility, and responsiveness, the MaaSAI System enables…

DATAWiSE

DATAWiSE Intelligent and Sustainable Building Management powered by Cross-Sectoral Lifecycle The overall objective of DATAWiSE is to develop and test building and building portfolio management tools, leveraging cross-sectoral lifecycle data, on the basis of an open, secure, interoperable, and scalable framework, to maximize both energy efficiency and stakeholder value. Utilizing cutting-edge artificial intelligence and advanced analytics, the methodology integrates data from a variety of sources to provide a holistic understanding of building operations. Besides technological innovation, the project also incorporates a supportive market and policy framework designed to offer evidence-based pathways for widespread adoption and commercialization. DATAWiSE aims to provide a standardized approach for managing and exploiting building-related big data. M4D is the coordinator of DATAWise project. It is also responsible for the scientific and technical management of the project,…

SEISMEC

SEISMEC Supporting European Industry Success Maximization through Empowerment Centred development SEISMEC pioneers a transformative approach to digital and industrial technology development, focusing on empowerment, human-centricity, and ethical principles. Through 17 pilot projects across 19 companies in 14 countries and diverse industrial sectors, SEISMEC aims to drive a paradigm shift. The project aims to demonstrate the concept of human-centricity in diverse industry sectors and contexts. Its objectives include empowering skilled workforces, addressing challenges related to advanced workplace technologies, and fostering innovation through evidence-based recommendations. SEISMEC stands as a landmark effort in reshaping European industry toward empowerment and human-centricity, with a strong emphasis on worker security and satisfaction The project evaluates the benefits of human-centricity across various dimensions such as creativity, collaboration, autonomy, and productivity, using CAPS empowerment factors introducing technical innovations…