The transition to the smart grid era is associated with the creation of a meshed network of data contributors that necessitates for the transformation of the traditional top-down business model, where power system optimization relied on centralized decisions based on data silos preserved by stakeholders, to a more horizontal one in which optimization decisions are based on interconnected data assets and collective intelligence. Consequently, the need for “end-to-end” coordination between the electricity stakeholders, not only in business terms but also in exchanging information is becoming a necessity to enable the enhancement of electricity networks’ stability and resilience, while satisfying individual business process optimization targets of all stakeholders involved in the value chain. SYNERGY introduces a novel reference big data architecture and platform that leverages data, primary or secondarily related to the electricity domain, coming from diverse sources (APIs, historical data, statistics, sensors/ IoT, weather, energy markets and various other open data sources) to help electricity stakeholders to simultaneously enhance their data reach, improve their internal intelligence on electricity-related optimization functions, while getting involved in novel data (intelligence) sharing/trading models, in order to shift individual decision-making at a collective intelligence level. To this end SYNERGY will develop a highly effective a Big Energy Data Platform and AI Analytics Marketplace, accompanied by big data-enabled applications for the totality of electricity value chain stakeholders (altogether integrated in the SYNERGY Big Data-driven EaaS Framework). SYNERGY will be validated in 5 large-scale demonstrators, in Greece, Spain, Austria, Finland and Croatia involving diverse actors and data sources, heterogeneous energy assets, varied voltage levels and network conditions and spanning different climatic, demographic and cultural characteristics.

ENFIELD will create a unique European Centre of Excellence that excels the fundamental research in the scientific pillars of Adaptive, Green, Human-Centric, and Trustworthy AI that are new, strategic and of paramount importance to successful AI development, deployment, and acceptance in Europe and will further advance the research within verticals of healthcare, energy, manufacturing and space by attracting the best talents, technologies and resources from world-class research and industry players in Europe and by carrying out top-level research activities in synchronisation with industry challenges to reinforce a competitive EU position in AI and create significant socio-economic impact for the benefit of European citizens and businesses. ENFIELD will develop, maintain, scale-up and sustain a vibrant European network on AI composed of 30 consortium members from 18 countries, including top-level education and research organisations, large scale businesses, SMEs, and public sector representatives jointly addressing critical issues of research and innovation frontiers in this new topic of the European AI Lighthouse. ENFIELD will provide high impact outputs such as >75 unique AI solutions (algorithms, methods, simulations, services, data sets and prototypes), 180 scientific high-impact publications and 200 peer-reviewed presentations, four strategic documents, namely the Common Research Roadmap and Vision, the dynamic Safety and Security Risk Assessment Framework, the White Paper and the Gender and Ethics Framework. The exchange and innovation schemes planned in Open Calls, which will grant financial support to >76 individual researchers and 18 small-scale projects, education, and training activities such as summer schools and hackathons, and a set of well-designed outreach methods and activities will further contribute to the ENFIELD community engagement, enlargement, and continuity.

LAZARUS is a three-year research and innovation project that aims to heal many of the security issues that befall modern software during its development lifecycle. The recently introduced area of DevSecOps - in medium to large companies - unfortunately lacks automated security tools, while most existing solutions are targeting only one narrow step of the SDLC process but miss a much needed holistic overview of the global security solution. LAZARUS innovates by intervening in multiple steps of the SDLC, performing targeted security checks and collecting valuable information and intelligence from each step, and exploiting advanced ML and AI methods to convert this intelligence into actionable insights and recommendations. The main innovations of LAZARUS are illustrated in the figure below. Moreover, we provide advanced features for developers, that employing our tools would be able to deploy more intelligent and distributed solutions through dedicated APIs. LAZARUS follows an open-source approach for the core functionality, which is supported by a realistic and viable business model for the sustainability and further exploitation of the project after it reaches the end of this financing phase. To validate the efficacy of the project outcomes we have secured two exciting real-world, diverse, pilots in two very different and demanding sectors.

Breast cancer is now the most common cancer worldwide, surpassing lung cancer in 2020 for the first time. It is responsible for almost 30% of all cancers in women and current trends show its increasing incidence. Neoadjuvant chemotherapy (NAC) has shown promise in reducing mortality for advanced cases, but the therapy is associated with a high rate of over-treatment, as well as with significant side effects for the patients. For predicting NAC respondents and improving patient selection, artificial intelligence (AI) approaches based on radiomics have shown promising preclinical evidence, but existing studies have mostly focused on evaluating model accuracy, all-too-often in homogeneous populations. RadioVal is the first multi-centre, multi-continental and multi-faceted clinical validation of radiomics-driven estimation of NAC response in breast cancer. The project builds on the repositories, tools and results of five EU-funded projects from the AI for Health Imaging (AI4HI) Network, including a large multi-centre cancer imaging dataset on NAC treatment in breast cancer. To test applicability as well as transferability, the validation with take place in eight clinical centres from three high-income EU countries (Sweden, Austria, Spain), two emerging EU countries (Poland, Croatia), and three countries from South America (Argentina), North Africa (Egypt) and Eurasia (Turkey). RadioVal will develop a comprehensive and standardised methodological framework for multi-faceted radiomics evaluation based on the FUTURE-AI Guidelines, to assess Fairness, Universality, Traceability, Usability, Robustness and Explainability. Furthermore, the project will introduce new tools to enable transparent and continuous evaluation and monitoring of the radiomics tools over time. The RadioVal study will be implemented through a multi-stakeholder approach, taking into account clinical and healthcare needs, as well as socio-ethical and regulatory requirements from day one.

In order to address the fast-evolving challenges with respect to advanced forms of cybercrimes enabled by fully available state-of-the-art technologies (Crime-as-a-Service), there is a need for LEAs to form and apply cutting-edge collaboration frameworks that will break communication silos within the wider judicial ecosystem. These frameworks may span in numerous pillars, such as (i) regulated, privacy-preserving and easy sharing of information related to criminal activities enabling cross-border agency-to-agency collaboration in a transparent and explainable manner; (ii) joint criminal investigation further facilitated by beyond state-of-the-art tools enabling real-time collaboration and the full exploitation of distributed digital infrastructures to enhance cybercrime intelligence; (iii) exchanging different types of expertise (cybersecurity experts, forensics experts, lawyers and stakeholders from the judicial ecosystem, psychologists, social scientists) to realise cutting edge investigative approaches; and (iv) knowledge and best practices sharing with respect to trainings and cybercrime awareness. GANNDALF will set new grounds for the fight against advanced forms of cyber threats and cyber-dependent crimes; it will (i) realise cutting-edge agency-to-agency data sharing mechanisms, optimising the balance between transparency and privacy based on the needs of each LEA; (ii) deploy a modular, decision-support toolbox that will comprise not only ground-breaking technologies for collaborative investigation, prediction and identification of advanced forms of cyber threats, but also optimisation mechanisms enabling the full exploitation of these technologies; (iii) build on the above 2 offerings and deliver a customizable, collaborative crime investigation sandbox for scenarios, hypotheses analysis and crime investigation; and (iv) facilitate policy drafting, training and citizens’ engagement via innovative mechanisms that will realise the Cyber Hygiene 2.0 visiοn.