THE PROVOST, FELLOWS, FOUNDATION SCHOLARS & THE OTHER MEMBERS OF BOARD, OF THE COLLEGE OF THE HOLY & UNDIVIDED TRINITY OF QUEEN ELIZABETH NEAR DUBLIN

VOICES aims to recover the voices and interrogate lived experiences of women in early modern Ireland. Ireland formed part of the British, European and Atlantic world and women there responded to similar sets of transformative processes as other early modern women - proto-globalisation, state formation, confessionalisation, warfare, commercialisation, environmental change, and so on – which facilitates interrogation that is comparative, connected, and entangled. Two ambitious research questions underpin this pioneering project which focuses on Ireland as a case study. (1) What role did women play in a society undergoing profound economic, political, and cultural transformation? (2) What were their experiences of recurring social upheaval, bloody civil war and extreme trauma, especially sexual violence, and how have these been politicised? Our novel approach derives in large part from the interrogation of previously inaccessible historical data, now available digitally. This windfall is exceptional, but the resulting data is unstructured. Innovative technologies transform this unstructured data into knowledge that can be interrogated and visualised. VOICES will then transform the field of history by allowing us to: • recover the marginalised voices, lifecycles, and identities of women in Ireland and assess their contribution to the household, regional and national economies; and relationship to the land (WPs1, 2); • situate the experiences of women in the broader analytical framework of Europe, Britain, and the Atlantic world (WPs1-4); • lay the foundations for further future scholarship on the family, gender, identity, memory, emotion, and trauma in the early modern period (WPs1-4); • produce ontologies that outline key concepts and entities that relate to women and violence that can be reproduced across time and place, which makes VOICES the exemplar of the new and longstanding research questions now answerable by digitisation and associated methodologies (WP0)

EC contribution:

EUR 2.5M

Start:

2023-09-01

End:

2028-08-31

Status:

SIGNED

Scheme:

HORIZON-ERC

Call:

ERC-2022-ADG

View on CORDIS (DOI 10.3030/101097003)

The main objective of the lorAI project is to upgrade the Kempelen Institute of Intelligent Technologies (KInIT) to a leading R&I institution in low resource artificial intelligence (LRAI) in Slovakia and Europe (with help of advanced partners – top European AI research institutes ADAPT, DFKI and CERTH). The core of lorAI’s impact stands on three pillars: 1) nurturing talent and personal capacities, 2) pursuing research excellence in low resource AI (LRAI), and 3) innovation and technology transfer with elaborated outreach programmes. LRAI represents a global research challenge yet is also relevant to the EU region by developing efficient AI operating with limited resources to increase AI availability (for society and industry) and environmental sustainability. Despite tackling the low complexity and computational costs of AI, Centre of Excellence will explore AI applications for the NLP and Green environment (i.e., domains of energy usage optimization, anomaly detection). The activities of the CoE are grouped into ten focused Excellence programs, which, in synergy, contribute to expected impacts overseen by the call and destination by increasing research capacities and competence, funding acquisition capacities, excellent research with societal and economic impact, engagement of industry and wider R&I ecosystem, and internationalization. Aligned to Slovak and EU strategies (e.g., Slovak Smart Specialization, Coordinated Plan on AI, Green Deal), the lorAI project builds on a unique opportunity of ongoing programs (e.g., EUs Recovery and Resilience), importance of AI and environmental challenges, to multiply effects of the measures resulting in improving Slovak R&I culture and stimulate reforms. Thanks to the CoE governance model, autonomy is guaranteed. The diversified budget reduces unexpected disruptions and with cross-cutting themes (international, interdisciplinary, cross-sectoral, transfer oriented) ensures long-term sustainability.

EC contribution:

EUR 1.2M

Start:

2025-03-01

End:

2031-02-28

Status:

SIGNED

Scheme:

HORIZON-CSA

Call:

HORIZON-WIDERA-2023-ACCESS-01

View on CORDIS (DOI 10.3030/101136646)

Management of food waste (FW) and petroleum plastics pollution are two significant global challenges. Developing biopolymers and added-value bioplastic products from low-grade FW is, thus, a key enabler to tackle both issues. Despite extensive R&D efforts to valorise waste streams including FW to bioplastics, the widespread market penetration of bioplastics is hindered due to their high production cost. BioLaMer aims to demonstrate a novel proof of principle fly larvae biorefinery by establishing food eating black soldier fly larvae (Hermetia illucens) as a high impact feedstock for cost-effective production of two biopolymers, polyhydroxyalkanoates (PHA) and chitosan. The advantages of the larvae route are that it: i) is renewable and inexpensive; ii) provides less complexity as the larvae has invariable chemical composition; iii) can be used to mitigate the FW problem; iv) can reduce raw material inputs, thus minimizing energy utilization; v) doesn’t disturb the biodiversity; and vi) can avoid/reduce pre-treatment costs associated with the waste-streams to produce the platform chemicals for biopolymer production. The innovative BioLaMer biorefinery will improve the bioreactor process efficiency and cut down the PHA production cost significantly compared to existing technologies. BioLaMer will combine its conceptual innovations, complementary interdisciplinary expertise and bioreactor process expertise to develop cost-effective PHA and chitosan production technologies, supported by life cycle thinking/analysis and hybrid models developed using machine learning platform. Further, the significant environmental, economic, and societal impacts (that supports the EU Circular Economy, Green Deal, Food Waste, and Plastic strategies/initiatives) of BioLaMer will be demonstrated through the involvement of SSH, communication and circularity demonstration partners.

EC contribution:

EUR 870k

Start:

2023-04-01

End:

2026-06-30

Status:

SIGNED

Scheme:

HORIZON-EIC

Call:

HORIZON-EIC-2022-PATHFINDEROPEN-01

View on CORDIS (DOI 10.3030/101099487)

In flIMAGIN3D, which centres on fluorescent lifetime imaging microscopy applied to biomedical platforms in 3D; ten talented Doctoral Candidates (DCs) will be recruited, trained and supervised to cohesively establish the most robust, user accessible and powerful FLIM-based platform-never achieved before, and apply it to a wide range of applications in the biological sciences. flIMAGIN3D will generate ten DCs at the cutting edge of FLIM-based biological imaging who will spearhead, and go onto catalyse clusters of FLIM excellence across Europe; each intertwined within a collaborative network that will extend beyond the time-frame of the program. This doctoral network will train talented doctoral candidates in the essential theories underpinning FLIM , and through the individual projects and extensive secondments in this network; elevate their projects and skills, and that of their secondment hosts to research excellence in FLIM flIMAGIN3D addresses a significant knowledge gap in the field of photonics in biology by involving biomedical scientists in each and every aspect of development and design, and cognisant of the wide variety of current platforms that require adaptability to such modalities. In flIMAGIN3D: bringing together representatives with different applications and backgrounds, we will identify and overcome barriers to FLIM imaging by developing the next generation of scientists who will develop a FLIM platform capable of extracting the greatest amount of information possible in a stream-lined, accurate and user-friendly manner in order to understand biology in disease, differentiation, development and interventions at a high resolution. To achieve this goal, the trained scientists will develop cheaper advanced hardware components, with user friendly software that can build precise libraries for accurate machine learning classifications and plug-and-play platforms and sensors to facilitate a wide range of applications.

EC contribution:

EUR 859k

Start:

2023-01-01

End:

2026-12-31

Status:

SIGNED

Scheme:

HORIZON-TMA-MSCA-DN

Call:

HORIZON-MSCA-2021-DN-01

View on CORDIS (DOI 10.3030/101073507)

The objective of HARNESS is to train a multidisciplinary cohort of 13 PhD students in an international Doctoral Network, specialising in ethics, law, and technology. The network will offer comprehensive training, supervision, and secondments, allowing individuals to become experts in their specific disciplines while gaining practical knowledge across various fields. The program is supported by an excellent team of partners who are world leaders in their respective domains. The ethical and socio-technical impacts of the current and forthcoming AI and data-intensive information systems (e.g. Common European Data Spaces) require careful multidisciplinary consideration and foresight techniques regarding their alignment with EU's values, sovereignty and economic and societal goals. The new European regulations on data and AI should be supported by robust methods and tools to empower citizens and civil society to swiftly comprehend, navigate, and address emerging threats to fundamental rights. HARNESS will analyse the joint impact of new AI and data-intensive technologies and their regulation, considering legal entanglements, new legal compliance tools and the consequences that can be anticipated, from ethical, societal and economic perspectives. AI and data legislation will be formalised and operationalised under the 'Law as Code' paradigm using international standards and semantic web technologies. Specific cases such as AI Foundational models, impact of new regulations on competitiveness and the interplay of self-sovereign identity in Common European Data Spaces will be analysed in detail. HARNESS will utilise and build upon the state of the art in open information systems and knowledge engineering to develop appropriate methodologies, tools, and taxonomies to assist with regulatory compliance, deliberation and agreement on ethical norms. This will involve charting the constellation of possible systems, anticipating new risks and developing effective mitigations.

EC contribution:

EUR 859k

Start:

2025-01-01

End:

2028-12-31

Status:

SIGNED

Scheme:

HORIZON-TMA-MSCA-DN

Call:

HORIZON-MSCA-2023-DN-01

View on CORDIS (DOI 10.3030/101169409)

6G envisions unprecedented requirements for immersive, hyper-reliable, ubiquitous and low-latency connectivity together with dynamic sensing and AI-native capabilities across diverse and complex propagation environments. However, traditional waveforms and signal processing methods struggle to meet these requirements, especially under high mobility, interference, scalability and energy efficiency constraints. Furthermore, exploitation of MIMO (multiple input, multiple output) antenna technologies such as extremely large antenna arrays causes energy consumption bottlenecks as the number of RF chains scales-up. Hence, significant new innovations in signal and waveform design/processing, will be needed to meet the ambitious sustainability, performance, and standardization and backward compatibility goals of 6G. To address these challenges, a new pan-European consortium has been established to put forth this proposal, bringing together leading experts from a range of complementary disciplines, including RF and analogue circuit design, antenna systems, multidimensional signal processing, machine learning, and communication networks.   MULTIPLY-6G aims to develop advanced multidimensional waveform technologies, low-complexity extreme large arrays, and advanced spectrum sharing techniques, in an Open RAN (O-RAN) framework. This approach could unlock unprecedented levels of area spectral efficiency, energy efficiency and communication link reliability for wireless networks beyond 5G. It explores a revolutionary approach towards multi-dimensional waveform processing/design, by channel representation in delay, Doppler, and wavenumber domains, ensuring compatibility with standard wireless protocols. ,

EC contribution:

EUR 587k

Start:

2026-06-01

End:

2029-05-31

Status:

SIGNED

Scheme:

HORIZON-JU-RIA

Call:

HORIZON-JU-SNS-2025-01

View on CORDIS (DOI 10.3030/101293106)

The RELAX European Doctoral Network aims to train a cohort of highly mobile and adaptable researchers to become experts in the design of scalable and efficient data-intensive software systems. These experts will master the specific skill of navigating the semantics or correctness conditions of applications, with the goal of enhancing scalability, response times, and availability. Working across the disciplinary specialisms of data science, data management, distributed computing and computing systems, the Fellows will develop knowledge of the broad issues underpinning data analytics systems. The bespoke training programme fosters intellectual enquiry and combines technical and scientific research training with courses in innovation, management and leadership. The training network addresses a critical skills gap in data analytics expertise, which needs urgently addressed to support innovation and employment in a fast-growing European data economy. The 14 partner organisations representing 8 countries will benefit first-hand through intersectoral collaboration and an Open Innovation model.

EC contribution:

EUR 573k

Start:

2023-03-01

End:

2027-02-28

Status:

SIGNED

Scheme:

HORIZON-TMA-MSCA-DN

Call:

HORIZON-MSCA-2021-DN-01

View on CORDIS (DOI 10.3030/101072456)

Women’s cardiovascular health is an urgent clinical unmet need as reported by the European Society of Cardiology (ESC), as cardiovascular disease (CVD) risk in women still tends to be underestimated by clinicians and women themselves. CVD is under-diagnosed, under-treated and poorly understood, more so in women in the 40-60 age group, when personalised risk assessment and prevention can have a positive impact on their health. In this context, CARAMEL will deliver an innovative personalised prevention model aimed at women 40-60yrs based upon a risk assessment stratification model considering sex and gender specific risk factors and a self-assessment and self-management approach using innovative digital technologies, empowering women to optimise their cardiovascular health. The proposed CVD-Risk Assessment and Stratification scheme will only be possible by the cumulative risk factors analysis, fueled by AI, emerging from a wide number of different data sources, including clinical data from EHR, medical imaging, biomarkers, metabolomics, lifestyle information (sleep, physical activity, diet) from large cohorts and biobanks. A consortium composed by 25 partners and Affiliated Entities coming from 11 countries, composed by 9 clinical entities, 6 research organisations and 10 industry and SMEs will develop, test and validate the personalised prevention program in observational and interventional studies in clinical sites in Colombia, Croatia, Greece, Lithuania and Spain. To that end, engagement of women aged 40-60, will take place from the onset on the co-design and co-creation of the studies and the self-management app ecosystem to be developed. Likewise, Gender in research will be mainstreamed all along the intervention. CARAMEL will also deliver policy recommendation and clinical guidelines supporting the design and update of CVD Plans by health authorities and healthcare providers, considering novel AI based risk models, applicable to women aged 40-60 yrs.

EC contribution:

EUR 508k

Start:

2024-12-01

End:

2029-11-30

Status:

SIGNED

Scheme:

HORIZON-RIA

Call:

HORIZON-HLTH-2024-STAYHLTH-01-two-stage

View on CORDIS (DOI 10.3030/101156210)

Artificial Intelligence (AI) is widely studied and finding increasing adoption across communication technologies spanning network layers and business ecosystems. It is anticipated to play a central role in the design and operation of future 6G networks. Despite the promise of AI, there remain many obstacles to its use in communication networks. The introduction of software defined elements such as radio access network (RAN) intelligent controllers (RIC) enables multi-party applications for the control and management of networks. However, AI functions are still nascent and such structures do not extend to optical networks or multi-controller environments. 6G-XCEL seeks to address these challenges through research on high edge network use cases that employ multi-party AI controls running over compute accelerators to coordinate control across radio and optical networks. It will develop a reference framework for AI in 6G that will pave the way towards global validation, adoption and standardisation of AI approaches. This framework will enable decentralised AI-based network controls across network domains and physical layers, while promoting security and sustainable implementations. Using the latest AI algorithms and data compression, research on the resulting decentralised multi-party, multi-network AI (DMMAI) framework will enable the development of reference use cases, data and model repositories, curated training and evaluation data, as well as technologies for its use as a benchmarking platform for future AI/ML solutions for 6G networks. 6G-XCEL will bring together a large ecosystem of researchers from the EU and US to implement elements of the DMMAI framework in their testbeds and labs, integrating it into their research programs and validating the framework across platforms. Working with standardisation groups within each jurisdiction, 6G-XCEL will achieve joint progress towards large scale application of AI in 6G networks.

EC contribution:

EUR 454k

Start:

2024-01-01

End:

2026-12-31

Status:

SIGNED

Scheme:

HORIZON-JU-RIA

Call:

HORIZON-JU-SNS-2023

View on CORDIS (DOI 10.3030/101139194)

The MOZART project aims to advance the state-of-the art in robotic handling and manipulation of soft and heterogenous objects. The approach we take is a radical departure from existing manipulator approaches as we will develop a new concept for manipulation through the use of deformable manipulation surfaces supported by AI-powered control and learning tools. The manipulation surface is able to change its curvature locally and through this manipulates objects on the surface. The manipulation surface has three constituent elements. A conventional modular electronics layer responsible for communication, power, and computation, an actuation layer based on origami mechanisms, and finally, a soft poro-elastic sensing skin. The hardware development is complemented by a distributed control application programming interface which is built on cellular automata and deep learning. The framework includes basic and coordination primitives that allow for manipulation of individual objects and groups of objects, respectively. For demonstration we have chosen three target demonstrators in the food handling industry which are descaling fish, sorting of chicken and presentation of chicken. The final pillar of the project is an integrative-interdisciplinary social sciences and humanities approach that tackles the transition of the role of the operators today to more high-skilled jobs in the future. It also addresses the general ethical challenges surrounding food production to ensure sustainable technology development in terms of social and ethical as well as ecological consequences. The core research is complemented by a comprehensive dissemination and communication package that targets all relevant stakeholders. Finally, a clear exploitation plan including standardisation is described which will transition the AUTOMATs from TRL 5 at the end of the project to a product ready to impact the food packing industry four year after the end of the project.

EC contribution:

EUR 449k

Start:

2022-10-01

End:

2026-09-30

Status:

SIGNED

Scheme:

HORIZON-RIA

Call:

HORIZON-CL4-2021-DIGITAL-EMERGING-01

View on CORDIS (DOI 10.3030/101069536)

The future of media experiences is still to be written, and the maturity of eXtended Reality (XR) and Artificial Intelligence (AI) technologies provides a unique window of opportunity for the European Creative and Cultural Sector (CCS) to reimagine digital co-creation, interaction and engagement possibilities. TransMIXR, a consortium of eight representatives from the CCS and twelve leading industrial and academic partners, combines the necessary interdisciplinary skillsets and domain expertise to create a range of human-centric tools for remote content production and consumption via social virtual reality. The project’s TransMIXR platform will provide (i) a distributed XR Creation Environment that supports remote collaboration practices, and (ii) XR Media Experience Environment for the delivery and consumption of highly evocative and highly-social immersive media experiences. The ground-breaking AI techniques for the understanding and processing of complex media content will enable the reuse of heterogeneous assets across immersive content delivery platforms. Using the Living Labs methodology, TransMIXR will develop and evaluate four pilots that bring the vision of future media experiences to life in four CCS domains: (i) news media & broadcasting, (ii) performing arts, and (iii) cultural heritage. Additionally, the project will harness the creativity of the CCS and will forge interdisciplinary collaborations to demonstrate how immersive social experiences could be transferred to new application areas beyond the CCS. The results of the project will contribute to the Media and Audiovisual Action Plan from the European Commission, in particular boosting the adoption of XR technologies, opening new business models opportunities in new application areas and markets, and gaining worldwide leadership in XR technologies while being deeply grounded in European values such as veracity, diversity, connectedness and universality.

EC contribution:

EUR 429k

Start:

2022-10-01

End:

2025-12-31

Status:

SIGNED

Scheme:

HORIZON-IA

Call:

HORIZON-CL4-2021-HUMAN-01

View on CORDIS (DOI 10.3030/101070109)

This project seeks to understand the interplay between writing and orality in Ancient Mesopotamia (c. 3400 BCE – AD 100): what was written down, what circulated only in the oral realm, aThis project seeks to understand the interplay between writing and orality in Ancient Mesopotamia (c. 3400 BCE – AD 100): what was written down, what circulated only in the oral realm, and why. The result will be a cohesive model of orality and writing in Ancient Mesopotamia, which will in turn shed light on ancient societies with less documentation, enabling a much-needed ‘leap forward’ in the study of ancient writing and orality beyond Mesopotamia alone. It will also open up a new sub-field within Mesopotamian studies, and offer new ways of thinking about Mesopotamian writings. MESOR’s goals will be met by three work packages. First, it aims to establish the facts about what sort of things were usually written down, and what sort of things were not; and about how this varied across time, place, context, and type of written document. Secondly, the project aims to interpret and explain the distribution which it identified. To take some simple examples: Why are there no cuneiform graffiti? Why do cuneiform sources hardly mention begging? What did and did not get embraced by the ‘written tradition’? The project will be the first time such questions are addressed in an organic and systematic way. Use will be made of wide-ranging ethnographic parallels. Thirdly, the project will work out the implications and applications of its findings. These extend across all aspects of the lived experience, from administration to education to religion. The project’s methods will unite traditional close reading with corpus-driven quantitative data analysis, and its investigation will transcend established disciplinary boundaries: it will combine Akkadian and Sumerian philology, the anthropology of reading and writing, the history of literacy studies, orality studies, and socio-cultural history.

EC contribution:

EUR 422k

Start:

2025-01-01

End:

2030-09-30

Status:

SIGNED

Scheme:

HORIZON-ERC

Call:

ERC-2023-ADG

View on CORDIS (DOI 10.3030/101142318)

FORSEE posits that the advancing technical capabilities of AI applications require a clear understanding of what successful AI means - for society as a whole - together with the conditions of possibility for successful AI. New AI technologies are sites of negotiation and contestation. Different groups, based on their social positions, develop diverse and possibly conflicting ideas on what constitutes “success”. Expanding visions that define AI strictly in terms of technological and economic efficiency, FORSEE aims to develop a nuanced and enriched notion of success that will guide future AI applications and policy efforts. To achieve this, FORSEE draws from the social construction of technology to engage with three categories of stakeholders: a) institutional actors, b) “lifeworld” stakeholders (Civil Society Organizations representing gendered perspectives and Digital SMEs) and, c) the broader public. Then, FORSEE inquires into the impact of AI applications on economy, society and sustainability as well as on their alignment with EU values and strategic priorities. These interconnected research projects will illuminate a broader understanding of success that rests upon conflict resolution, empowerment of stakeholders, and alignment with fundamental rights and the goal of sustainable development. Based on these research findings, FORSEE will (i) develop a novel approach to AI governance that can guarantee more successful AI applications for society as a whole, including (ii) a new evaluative framework for assessing current and future AI applications, and (iii) a new prototype for registering risk and negative impacts. Through these outputs, FORSEE highlights and analyses existing successful AI applications to strategically enhance capabilities of our stakeholders and policymakers to address future risks and opportunities. Updating the SME sector’s understanding of success is a particular condition for the EU to retain a leading position in the AI landscape.

EC contribution:

EUR 398k

Start:

2025-02-01

End:

2028-01-31

Status:

SIGNED

Scheme:

HORIZON-RIA

Call:

HORIZON-CL2-2024-TRANSFORMATIONS-01

View on CORDIS (DOI 10.3030/101177579)

AI and big data are fundamentally interwoven into our societies, culture and indeed into our expectations and conceptions of democratic governance and exchange. They can also, however, contribute to an environment for citizens that is distinctly anti-democratic. KT4D will harness the benefits of an understanding of these as knowledge technologies to foster more inclusive civic participation in democracy. To achieve this, we will develop and validate tools, guidelines and a Digital Democracy Lab demonstrators platform. These results will be validated across three user needs scenarios: 1) building capacity for citizens and citizen-facing Civil Society Organisations (CSOs); 2) creating regulatory tools and services for Policy and CSOs; and 3) improving awareness of how to design ethically and mindfully for democracy principles in academic and industrial software development. Our work is underpinned by the understanding that to fully address the social and fundamental rights costs of AI and big data, we need more than just technological fixes, we need more than just technological fixes, we need to address the underlying cultural influences and barriers. Most importantly, we understand the threats to democracy of AI and big data not only through the nature of what they do, but via the cultural disruptions they create with power dynamics they shift, their tendency toward opacity, and the speed at which they change. KT4D’s ambitious and disruptive results will drive transformation in how democracy and civic participation are facilitated in the face of rapidly changing knowledge technologies, enabling actors across society to capitalise on the many benefits these technologies can bring in terms of community empowerment, social integration, individual agency, and trust in both institutions and technological instruments, while confidently mitigating potential ethical, legal and cultural risks.

EC contribution:

EUR 374k

Start:

2023-02-01

End:

2026-01-31

Status:

SIGNED

Scheme:

HORIZON-RIA

Call:

HORIZON-CL2-2022-DEMOCRACY-01

View on CORDIS (DOI 10.3030/101094302)

COALESCE aims to develop a cross-optimization platform that enables integrated operation and interplay between the energy grids and the data and telecommunication networks. Telecommunication and data networks need energy, while energy grids need data to operate efficiently. This project will develop a framework that will optimize the interplay between energy grids and telecommunications and data networks in a way that both the infrastructure pillars (energy and telecommunications) are jointly sustainable and efficient. Through the Staff Exchange program, we will be able to exchange expertise and know-how between energy, data and telecommunications sectors across both academia and industry. We will assess how the proposed architecture performs by validating the framework against 4 use case scenarios; a) To investigate optimization algorithms for energy efficiency under simultaneous wireless information and power transfer (SWIPT) will be investigated in a local energy system context for a wireless sensor network. b) To develop a novel framework for predicting and validating trading optimization strategies for in-house energy asset management, considering battery storage, flexible domestic demand, windfarm, solar cells etc,. using neural network and transfer learning-based models; while maintaining sustainable and secure exchange of data and user (or individual residence) portfolio. c) To design novel set of measurement methodologies for the characterization of 5G/6G RAN's energy consumption and open data sets for analysis, parametric models of the energy consumption transfer function for the uplink and downlink and generative neural network models of the energy transfer function for the uplink and downlink. d) To formulate joint data-energy-transportation robust/stochastic optimization algorithms considering computational load flexibility, intermittent energy generation and storage and multi-agent learning algorithms for collaborative e-transportation and SLES.

EC contribution:

EUR 267k

Start:

2023-12-01

End:

2027-11-30

Status:

SIGNED

Scheme:

HORIZON-TMA-MSCA-SE

Call:

HORIZON-MSCA-2022-SE-01

View on CORDIS (DOI 10.3030/101130739)

Advanced materials R&D is crucial to finding solutions for a sustainable future and a competitive European economy. We need innovative materials to address societal challenges such as climate change, technological progress and resource scarcity. However, the current fragmentation in materials science and engineering in Europe hampers collaboration and slows down innovation. MaterialsCommons is a pioneering project designed to address these critical challenges by creating a federated digital infrastructure for advanced materials. This infrastructure connects researchers from both industry and academia while linking currently isolated resources. MaterialsCommons enables cross-sector collaboration and gives unprecedented access to materials and process data for all users, from materials discovery and synthesis to original equipment manufacturers. The technical solution is a machine-actionable multi-node ecosystem, centred around a user-friendly MaterialsCommons web entry point. MaterialsCommons will be a living ecosystem with a variety of tools and services to meet the needs of diverse advanced materials communities. Comprehensive, well-documented schemas will be established, together with terminologies, taxonomies and ontologies that serve as a common language across the broad materials community. An interoperable framework for combining existing workflow environments and corresponding software tools will be provided, making each individual node in the development chain FAIR, machine readable and actionable, and reproducible. The consortium includes 26 academic partners, 21 associated partners and 12 associated collaborators mostly from industry. Six strategically selected use cases from key industrial sectors ensure that the final solution fully meets all user needs, both academic and industrial. Mechanisms will be set up to ensure the long-term sustainability, among others by partners formally committing to continue the infrastructure beyond the project.

EC contribution:

EUR 204k

Start:

2026-06-01

End:

2030-05-31

Status:

SIGNED

Scheme:

HORIZON-IA

Call:

HORIZON-CL4-2025-01

View on CORDIS (DOI 10.3030/101293545)

Up to one fifth of young people report that they have experienced unusual perceptual experiences, thoughts or beliefs. These experiences (which we call Psychotic Experiences or PE) can take the form of hearing voices or seeing visions or feeling paranoid or believing things that are not true. As part of my ERC Consolidator Award (iHEAR), I and my team have learned a great deal more about these experiences and what they mean for young people. We know that these experiences can be transitory in most cases but that in some young people they recur throughout adolescence and adulthood. We know that, for some young people, these experiences can be associated with poor functioning and poorer mental health but for others they are not pathological. We have identified the need for an instrument that can differentiate between pathological and non-pathological psychotic experiences. This will support early risk screening and development of interventions among those who experience PE. We propose to search for natural language patterns within self-reported PE that are associated with high and low levels of mental ill-health. Our hypothesis is that young people’s first person account of their experiences are likely to contain natural language phrases that could be used to differentiate between PEs that occur in the context of mental ill-health are likely to require intervention and those that do not. Knowledge of natural language patterns for PE would be a valuable step in improving assessment tools in clinical practice. Additionally this could be a valuable new resource for digital tools and e-Health which is a growing area for mental health.

EC contribution:

EUR 106k

Start:

2024-01-01

End:

2026-12-31

Status:

SIGNED

Scheme:

HORIZON-ERC-POC

Call:

ERC-2022-POC2

View on CORDIS (DOI 10.3030/101100943)

RES-Q+ will build on the success of RES-Q (REgistry of Stroke Care Quality) - currently, used by many EU countries and 74 worldwide - to improve stroke care quality by collecting and analyzing hospital discharge reports. RES-Q+ will revolutionize these improvements by capturing the whole patient pathway. The solution will combine NLP with a clinically-validated semantic model to automate ingestion of hospital discharge reports in different languages and assist with audit and feedback. This will include creating a standard model for such reports and using AI to impute missing data. Further augmentations include the creation of two novel AI voice assistants, one to help patients provide feedback on their health and the other to help physicians provide high quality care. We will integrate all these tools into RES-Q+. This will be the basis for a European Open Stroke Data Platform, an open research platform for data aggregation, semantic harmonization and interoperability across European countries to promote the use and re-use of health data. We will facilitate efforts to define a standard European Stroke Hospital Discharge Report Exchange Format as a tool for better secondary use of data and healthcare in general. Consortium legal partners will develop a comprehensive legal and ethical toolbox as guidance towards legal compliance. This will boost wider adoption of such novel AI-based solutions by integrating all current and proposed Union legislation. Our clinical partners will provide medical records and steer the development to maximize clinical utility and validate final solutions. RES-Q+ will be deployed globally to solidify our position as European and global leader in quality improvement. Eventually we will guarantee citizens a similar level of quality control during hospitalizations as when flying in a commercial plane.

EC contribution:

EUR 51k

Start:

2022-11-01

End:

2026-10-31

Status:

SIGNED

Scheme:

HORIZON-RIA

Call:

HORIZON-HLTH-2021-TOOL-06

View on CORDIS (DOI 10.3030/101057603)

Based on previously developed models and an existing prototype of a clinical decision support system (patent pending), we set out in this project to further develop, test, and validate this clinical decision support for the treatment stratification of acute stroke patients to improve patient outcome. Machine learning (ML)-enabled Artificial intelligence (AI) methods are increasingly adopted in the medical field. Implementing ML-based CDSSs have the potential to be go beyond the current clinical state-of-the-art as AI excels at finding complex and non-linear relationships across a multitude of prognostic variables. AI also has the promise to combine different modalities, such as imaging and clinical values, leading to powerful stratification tools accounting for a multitude of patient sub-populations. Our consortium combines excellence in technical and medical machine learning development with the clinical expertise of three leading stroke hospital partners. Additionally, our consortium benefits from the special expertise in the development of trustworthy AI, software design, and the translation of AI models to the clinical setting with focus on the regulatory process. By leveraging the available medical data and exploiting technological opportunities in the field of AI, and developing and validating trustworthy AI solutions to be implemented in the clinical workflow we are seeking to surpass the clinical state-of-the-art by making a significant and sustainable impact on the treatment of acute stroke that will improve patient survival, outcome and quality of life. The results of our work will serve as a pathway for future projects and we will make our experiences public in the form of standard operating procedures (SOPs) in the areas of development, testing, validation, and regulatory processes.

EC contribution:

EUR 47k

Start:

2022-05-01

End:

2026-04-30

Status:

SIGNED

Scheme:

HORIZON-RIA

Call:

HORIZON-HLTH-2021-DISEASE-04

View on CORDIS (DOI 10.3030/101057263)