Data-Gouv-ML/pcri-informations-sur-les-projets-laureats huggingface dataset:
A Principled Plan to Prevent Transient Execution Attacks (Ghostbuster)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Advanced grants
Action type: ERC actions
Panel: Computer Science and Informatics
Panel description: Informatics and information systems, computer science, scientific computing, intelligent systems
Countries involved: Netherlands
Call: ERC ADVANCED GRANTS (ERC-2023-ADG, 2023)
Start date: 2025-01-01
End date: 2029-12-31
Duration (months): 60.0
Total project cost (EUR): 2499995.0
EU funding (EUR): 2499995.0
Participants: 1
Project status: SIGNED

Ghostbuster is a research program to stop advanced “transient execution attacks”, which by themselves already rank among the most advanced attacks ever—by finding vulnerable code fragments, analyzing them for exploitability, and injecting mitigations where needed. The vulnerabilities such as Spectre, Meltdown and others originate in vulnerable hardware and allow data leakage across all security boundaries. Recently, my team and I showed that even more advanced attacks exist by combining transient execution with traditional software exploitation. Today, we have no way of even detecting these hybrid attacks, let alone stop them. While we keep finding new variants, vendors have indicated that they cannot fix them all, as it would cripple performance. The hope is that developers identify and harden vulnerable code snippets (e.g., with instructions that stop transient execution). Unfortunately, finding vulnerable snippets is hard, beyond the abilities of top programmers, and even more so for the new hybrid attacks. Can it be done automatically? The challenge is daunting and involves all interaction between the code and a myriad of obscure CPU resources, requiring expertise in hardware, operating systems, fuzzing, program analysis, etc. State-of-the-art (and limited) tools do not even aim for mitigation and simply report potential issues—with many false positives and negatives. Unlike existing solutions that detect the snippets through pattern matching, Ghostbuster takes a principled approach and considers the fundamental conditions enabling attacks—without resorting to, say, symbolic execution, which scales poorly to large programs. It models the fundamental conditions of (steps of) an attack in terms of control + dataflow properties and translates the models into detectors. After detecting the code that looks vulnerable, it runs additional (possibly heavy-weight) exploitability analysis and, if need be, mitigates the issue by removing some of the enabling conditions

Keywords: transient execution micro architectural attacks and defenses
Using Predictions for Language Acquisition: New Neuroscientific Directions (UPLANDS)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Netherlands
Call: MSCA Postdoctoral Fellowships 2022 (HORIZON-MSCA-2022-PF-01, 2022)
Start date: 2024-02-01
End date: 2026-04-30
Duration (months): 27.0
Total project cost (EUR): 203464.32
EU funding (EUR): 203464.32
Participants: 1
Project status: SIGNED

Although we often regard language acquisition as an automatic process, there can be huge variation in the speed and success of different learners. As a good command of language is essential for many life outcomes, it is crucial to understand the mechanisms that lead to successful language acquisition. Some influential theories point to prediction-based learning as a crucial language acquisition mechanism. Prediction, the ability to anticipate other’s upcoming words or actions, is already known to play an important role in human communication. For instance, predicting when our conversation partner will stop speaking allows us to start our responses immediately, thus leading to fluent conversations. A prediction-based mechanism is at the heart of error-based theories of language acquisition, which suggest that children and adults constantly predict the next word when listening to others talk. They then assess whether their predictions were correct and if not, an error-signal is created which is then used for learning. While these theories have grown immensely influential in recent years, we still know little about the prediction-based mechanism that underpins them. We have limited evidence connecting linguistic predictions to language learning, and almost no direct knowledge of how a prediction-based language acquisition mechanism might operate. As a result, and despite the popularity of error-based theories of language acquisition, prediction’s actual role in language acquisition remains unclear. This project will significantly expand our current knowledge of how a prediction-based learning mechanism functions. It will do so by combining a newly-developed behavioural paradigm with neuroscientific methods (EEG and MEG) across three experimental studies. This will not only shed further light on prediction’s role in language acquisition, but will also establish a methodological approach that can form the basis of future research into these questions.

Keywords: language development prediction error based learning psychology of language
Women Building Brazil: a history of architecture from the perspective of self-building sites. (WBB)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Social Sciences and Humanities
Countries involved: Belgium,Brazil
Call: MSCA Postdoctoral Fellowships 2023 (HORIZON-MSCA-2023-PF-01, 2023)
Start date: 2024-09-01
End date: 2026-08-31
Duration (months): 24.0
Total project cost (EUR): 191760.0
EU funding (EUR): 191760.0
Participants: 2
Project status: TERMINATED

Women Building Brazil (WBB) seeks to underscore women’s contributions to architecture and construction in Brazil, particularly in contexts of self-building. Its main objective is to address the neglect of both women and informal building practices in architectural and construction history, especially in the global South. The project will tackle that double historical gap by gathering personal stories and documentation on women builders. Its premise is that women’s involvement in self-construction was actually quite common in vernacular architecture but has been affected by the introduction of new building technologies and materials. Expanding our disciplinary scope to include vernacular contexts, WBB employs a novel method combining oral history with disruptive archival research methods and community-based participatory practices, guided by feminist and decolonial principles. This approach will be applied in three territories in Brazil where self-building remains a prevalent custom: quilombos (afro-Brazilian maroon communities), indigenous territories and favelas (urban informal settlements). These distinct settings offer new insights to help recover, analyse, and acknowledge women’s construction know-how. The outcomes of WBB include an oral history archive and a public video collection. The participatory process will also generate a memory artefact, co-created with interviewed women with the purpose of recognizing their expertise and strengthening their building autonomy. In summary, WBB offers a new methodological approach to a growing field of construction history and a gendered analysis that contributes to the broader discipline of architectural history. It maintains a commitment to open science through its research methodology and participatory practices, ensuing constant dissemination of its results. Most importantly, WBB actively seeks ways of empowering women in construction, giving them voice and reaffirming the relevance of their know-how.

Keywords: construction history,decoloniality,tacit knowledge,brazil,self construction,vernacular architecture
Technologies for Manufacturing as a Service Ecosystems (Tec4MaaSEs)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Digital, Industry and Space
Theme: Industry
Destination: Climate neutral, Circular and Digitised Production
Action type: Research and Innovation actions
Partnership: Made in Europe (co-programmed)
Countries involved: Italy,Greece,Germany,Spain,Türkiye,Norway
Call: Achieving resiliency in value networks through modelling and Manufacturing as a Service (Made in Europe Partnership) (RIA) (HORIZON-CL4-2023-TWIN-TRANSITION-01, 2023)
Start date: 2024-01-01
End date: 2026-12-31
Duration (months): 36.0
Total project cost (EUR): 5932343.75
EU funding (EUR): 5932343.75
Participants: 13
Project status: SIGNED

Tech4MaaSEs derives inspiration from industrial challenges, scientific inquiries, and societal needs. At its core, Tech4MaaSEs develops a network of Digital Twins that possess both trustworthiness and cognition, allowing them to work collaboratively within a distributed value network. This network of Digital Twins is a key enabler for Manufacturing-as-a-Service (MaaS), where production and anufacturing are offered as a service. Tec4MaaSEs provides a comprehensive DT-based framework for value networks, which enables greater resilience and sustainability across the entire value network with continuous evaluation and monitoring of performance through a multilevel balanced scorecard system. Highly configurable, the solution is able to respond to the varying supply and demand of individual stakeholders. This flexibility makes it possible to evaluate alternatives and react appropriately, while improving the understanding of the impact of external disruptions. The project will deliver innovative business models that ensure adequate level of trust among the involved stakeholders, and flexible adaptation of production capabilities, sharing of resources and assets and coordination of individual value creation activities in the value network. A complementary Governance Framework improves oversight and control of the underlying industrial operations. Governance is declined along three dimensions: Business Governance, for operational and procedural aspects and applicable resource sharing strategies. Data Governance, addressing confidentiality, data sharing polices, data authorization/ownership/ etc, and AI models governance - how human centred-AI models ensure trustworthiness and AI explainability. The solution will be validated in three real value networks demonstrating the improved resilience and sustainability of the solution.

Keywords: maas,actionable models,sustainable and resilient value networks,digital twins,balanced score cards,smart manufacturing,dynamic configuration,governance,explainable ai
Personalised Risk Evaluation and Diagnosis in Cardiovascular Treatment for Acute Coronary Syndrome (PREDICT-X-ACS)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Information Science and Engineering
Countries involved: Malta,Germany,India
Call: MSCA Postdoctoral Fellowships 2024 (HORIZON-MSCA-2024-PF-01, 2024)
Start date: 2026-01-01
End date: 2028-06-30
Duration (months): 30.0
Total project cost (EUR): 256642.8
EU funding (EUR): 256642.8
Participants: 4
Project status: SIGNED

The Predict-X-ACS project, led by Dr. Deepa Joshi under the supervision of Prof. Lalit Garg at the University of Malta (UoM), aims to address the global burden of Acute Coronary Syndrome (ACS), a major contributor to cardiovascular disease (CVD). ACS, which results from the sudden reduction or blockage of blood flow to the heart, remains a leading cause of morbidity and mortality worldwide. This research integrates diverse data sources, including medical imaging, genomics, clinical records, environmental factors, and biomarkers, into a transformer-based, AI-powered precision medicine approach to enhance ACS care. The primary objective of the project is to develop scalable, explainable AI models that improve the diagnosis, treatment, and personalization of ACS care by overcoming the limitations of single-modal, non-transparent diagnostic tools. Through this multi-modal methodology, clinicians will be equipped with actionable insights, facilitating more accurate, individualized treatment plans and better patient outcomes. The project aligns directly with Sustainable Development Goal 3 (Good Health and Well-being) by contributing to the reduction of ACS-related mortality and improving patient care through the use of advanced medical technology. It also supports Sustainable Development Goal 9 (Industry, Innovation, and Infrastructure) by driving innovation in healthcare technology and promoting the application of cutting-edge AI methods in clinical practice. Continuous clinical validation and real-time feedback mechanisms ensure that the developed AI models are robust, adaptable, and ready for broad clinical implementation.

Keywords: acute coronary syndrome acs explainable ai xai multi modal data integration personalised treatment precision medicine
Identifying the role of injury-associated cellular reprogramming in the early oncogenic transformation of human colonic epithelium (PreCODE)

Framework: Horizon Europe — Excellent Science
Programme: Marie Skłodowska-Curie Actions (MSCA)
Theme: Marie Skłodowska-Curie
Destination: Postdoctoral Fellowships
Action type: Marie Skłodowska-Curie actions
Panel: Life Sciences
Countries involved: Denmark
Call: MSCA Postdoctoral Fellowships 2021 (HORIZON-MSCA-2021-PF-01, 2021)
Start date: 2023-09-01
End date: 2025-08-31
Duration (months): 24.0
Total project cost (EUR): 214934.4
EU funding (EUR): 214934.4
Participants: 1
Project status: CLOSED

Colorectal cancer represents a major public health problem being the second leading cause of cancer-related deaths worldwide. The treatment management of the already developed disease is however often time-consuming, expensive and rarely 100% effective. Therefore, the goal should be to start diagnosing and managing the diseased state as early as possible when cancer is still curable. The early cellular transformation events remain poorly understood as cancer-associated mutations have been found to be surprisingly prevalent in seemingly healthy tissues, suggesting the requirement for a potent trigger mechanism. With this project, I aim to study the early colonic transformation via a completely unique hypothesis and approach. My strategy is built on the emerging new “injury-triggered fetal-like state” concept guided by my host lab and the hypothesis that oncogenic mutations require transcriptional reprogramming to a more susceptible fetal-like state to trigger transformation. This hypothesis relies on the fact that the fetal-like state is observed during injury and also in subsets of tumors indicating that cellular reprogramming could play a prominent role in promoting oncogenic transformation. As a primary model system, I will make use of my extensive experience with cancer modeling via 3D human-derived organoids and CRISPR technology, and elevate these techniques by the state-of-the-art expertise available at the host lab and/or institution, such as in vivo orthotopic cell transplantation, epigenetic profiling, advanced CRISPR-screening methodology and clinical collaboration. By bringing together such intelligent methodology, I will be able to effectively investigate the role of injury-induced cellular reprogramming in the transformation of human colonic epithelium. The results of this work will shape the future directions of my own prospective lab, but also cancer research in general, promising major new implications on early cancer detection strategies.

Keywords: human,3d colonic organoids,crispr,colorectal cancer,injury,fetal like state,epigenetics
Understanding the psychology of the manosphere and how to protect young people from its negative influence (HATESHIELD)

Framework: Horizon Europe — Excellent Science
Programme: European Research Council (ERC)
Theme: European research council
Destination: Consolidator grants
Action type: ERC actions
Panel: The Soci al World and Its Interactions
Panel description: Sociology, social psychology, education  sciences , communication  studies
Countries involved: United Kingdom
Call: ERC CONSOLIDATOR GRANTS (ERC-2024-COG, 2024)
Start date: 2025-08-01
End date: 2030-07-31
Duration (months): 60.0
Total project cost (EUR): 1973814.0
EU funding (EUR): 1973814.0
Participants: 1
Project status: SIGNED

In the last 10 years, online misogyny has increased at an alarming rate. Social media influencers within the ‘manosphere’ preach that women are fundamentally inferior to men and ought to be subordinated to them. Women are derogated as innately illogical, greedy and scheming. These attributions are used to justify harassment, coercive control and discrimination. Teenagers, who get much of their news and entertainment from social media, are bombarded with this content on a daily basis. Teachers, parents and elected officials report grave concerns about the ways in which misogynistic influencers are affecting the attitudes of young people, particularly teenage boys. Developmental psychology provides a solid foundation for understanding the emergence of gender stereotypes and attitudes across childhood. However, it has struggled to keep pace with the rapidly expanding influence of social media and how it is affecting young people. A novel approach is needed. HATESHIELD will uncover the social dynamics of the manosphere and use this understanding to protect young people from its negative influence. The project will achieve four aims. First, use cutting-edge methods from AI to characterise the nature of adolescents’ interaction with online misogyny and pinpoint the age at which they are at greatest risk of exposure. Second, understand how interaction with online misogyny predicts changes in adolescents’ gender attitudes, homophobia and self-worth over time. Third, develop and rigorously evaluate strategies to prepare young adolescents (aged 12 – 13) to critically engage with online misogyny. Finally, develop and rigorously evaluate strategies to mitigate the deleterious effects of online misogyny on young adults (aged 18 – 25) who have already embraced some of its key messages.

Keywords: child development social cognition stereotyping sexism
AtoMik® - From racks to miniature modules: a disruptive leap for ultra-fast electronics testing (AtoMik)

Framework: Horizon Europe — Innovative Europe
Programme: The European Innovation Council (EIC)
Theme: EIC Accelerator
Destination: Other destinations
Action type: EIC actions
Countries involved: Sweden
Call: EIC Accelerator 2025 - Short application (HORIZON-EIC-2025-ACCELERATOR-01, 2025)
Duration (months): 30.0
Total project cost (EUR): 2500000.0
EU funding (EUR): 2500000.0
Participants: 1
Project status: CLOSED

Mikrodust AB is a Swedish deep-tech SME advancing Europe’s electronics manufacturing with its AtoMik® platform—a modular, automation-ready test ecosystem replacing bulky, closed ATE systems with compact, reconfigurable hardware, open software, and connected cloud services. The first-generation AtoMik® is already validated in industrial pilots and commercial use, with over 200 clients achieving up to 75 % faster testing and more than 4× higher throughput for leading OEMs and EMS providers. Building on this proven foundation, the EIC Accelerator project will develop the next-generation AtoMik®—a major technological leap that expands voltage and power capacity, introduces new high-performance modules and instruments, and integrates intelligent software and a cloud portal for connected data management. This generation will deliver parallel testing, real-time traceability, and full CE/ISO certification—positioning AtoMik® as Europe’s reference platform for high-throughput electronics validation. Mikrodust targets OEMs, EMS providers, and system integrators in IoT, industrial, energy, and defense sectors. Its business model combines hardware sales, software subscriptions, and service contracts, scaling through a partner-led “Mikrodust-inside” network of certified integrators. Competing with U.S. incumbents such as NI and Keysight, AtoMik® provides a European alternative that is modular, open, and cost-efficient. Developed and manufactured in Sweden, AtoMik® strengthens European technological sovereignty under the EU Chips Act, Industry 5.0, and Green Deal agendas. Backed by a high-performing team and more than 200 deployed systems, Mikrodust is ready to scale a next-generation solution that will empower faster, cleaner, and smarter production across Europe—reducing reliance on non-EU suppliers, cutting test-energy use, and strengthening Europe’s advanced manufacturing base.

Keywords: modular test system,automated test equipment,high throughput validation,industry 5 0,eu chips act,cloud integration,scalability,energy efficiency,digital autonomy,electronics manufacturing
INTEGRATING SUSTAINABLE MOBILITY AND LOGISTICS WITH CITIZEN-CENTRIC INTELLIGENT SOLUTIONS FOR SAFE, SMART, GREEN, RESILIENT, AND INCLUSIVE CITIES (BIO-INTEL-MOB)

Framework: Horizon Europe — Global Challenges and European Industrial Competitiveness
Programme: Mission
Theme: Climate neutral and smart cities
Destination: Climate neutral and smart cities
Action type: Innovation actions
Countries involved: Italy,Portugal,Netherlands,Belgium,Germany,Greece,Latvia,Ukraine,Türkiye,Switzerland,Croatia,Czechia,Lithuania
Call: Integrated peri-urban areas in the transition towards climate neutrality (HORIZON-MISS-2024-CIT-01, 2024)
Start date: 2026-01-01
End date: 2029-06-30
Duration (months): 42.0
Total project cost (EUR): 9491796.2
EU funding (EUR): 8965812.5
Participants: 32
Project status: SIGNED

BIO-INTEL-MOB aims to revolutionize peri-urban mobility, logistics, and governance through AI-driven, citizen-centric, and climate-neutral solutions. Addressing fragmented mobility networks, inefficient logistics, and governance gaps, the project integrates Advanced Mobility Data Space (aMDS), Peri-Urban Mobility Hubs (PUMHs), Green-Safe Routing Algorithm (GSRA), bio-packaging logistics units (bioPLU), and Digital Twin ecosystems. By leveraging AI-powered risk detection, emission monitoring, real-time analytics, multimodal transport optimization, and VR/AR-enabled participatory governance, BIO-INTEL-MOB enhances urban-peri-urban accessibility and connectivity, reduces private car dependency by 35%, and optimizes multimodal transport efficiency by 35%. The project’s interventions will lead to a 30% reduction in urban-peri-urban congestion, a 25% decrease in logistics-related emissions and packaging waste. Further, BIO-INTEL-MOB will cut VRU-related accident risks by 35%, improve air quality and noise pollution by 20%, and reduce the human health impact of transport-related pollution by 30%. The project conducts large-scale pilot demonstrations in Rome, Cascais, Riga & Vilnius, alongside satellite pilots in Melsungen, Ciampino, Urla, and Rhodes, ensuring scalability and transferability. Through policy-aligned smart city governance (SCGo) with policy engine, citizen-voice-app and knowledge-hub, and AI-driven multimodal transport innovations, BIO-INTEL-MOB strengthens citizen participation in city planning by 40%, creating data-driven and participatory ecosystems. The project’s AI-driven models will ensure a 40% increase in participatory governance efficiency, 25% faster policy compliance processes, and a 35% improvement in co-designing of city policies and infrastructure. The outcomes contribute to the EU Green Deal, Digitalization Strategy, and Climate-Neutral Cities Mission, positioning peri-urban areas as resilient, connected, and low-emission living spaces.

Keywords: city mobility and logistics and governance,peri urban mobility hubs,green safe routing,bio packaging logistics unit,smart city governance,citizen voice,policy compliance engine