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Call for Nominations: ELIAS Alliance FROntier AI Award

Call for Nominations: ELIAS Alliance FROntier AI Award

May 5, 2026 | ELIAS Alliance, Opportunities

The ELIAS (European Leadership in Innovation with AI and Science) Alliance invites nominations for the FROntier AI Award, recognizing outstanding AI leaders of Focused Research Organizations—including startups, nonprofits, and open-source consortia—who are building private or public frontier AI systems for meaningful value creation. 

Purpose of the Award

The purpose of the FROntier AI Award is to identify role models who inspire mentors and students in academia intellectually to pursue value creation through AI. It highlights AI leaders who successfully link academia with real-world impact, demonstrating that frontier research and practical value creation can go hand in hand.

The inaugural ELIAS Alliance award was presented to Max Welling for founding Cusp AI at the AI Summit AIS25 in Copenhagen under the Danish EU Presidency, marking a commitment to strengthening the connection between academic excellence and societal impact in Europe’s AI ecosystem.

Read more about AI Summit here: AI in Science Summit 2025: Europe Signals Ambition, Urgency, and Unity in AI for Science

ELIAS@AIinScience_4

Who Should Be Nominated

We seek individuals who:

Lead (Individuals or Team) a Focused Research Project (FROntier AI)

Demonstrate exceptional vision and execution in advancing frontier AI

Act as role models for translating research into meaningful value creation

Evaluation Criteria

Nominations will be assessed based on:

  • Value Creation & Frontier Impact – demonstrated potential for meaningful and sustainable real-world impact, while advancing the frontier of AI research, technology, or application.
  • Integrity & Responsibility – commitment to trustworthy AI development and to creating a positive and healthy societal impact.
  • Inspirational Leadership – ability to inspire, mentor, and motivate the next generation of researchers, founders, and innovators.
Nomination Process

Submissions should include:

  • 1 Page description of (1) the FRO and its mission and (2) the leading team or individual who can serve as role model for academic value creation
  • Supporting materials (e.g. systems, publications, impact evidence)
  • Short bio of the nominee(s)
    Timeline

      About ELIAS Alliance

      The ELIAS Alliance is dedicated to strengthening the European AI ecosystem by connecting research, industry, and society, and by promoting innovative organizational models that accelerate impactful AI development.

      Submit nominations to:

      elias-coordination@tuebingen.ai, ELIAS Alliance Coordinator, Lisa Schoellhammer

      We encourage nominations that reflect bold thinking, strong execution, and a deep commitment to using AI for meaningful impact.

      ELIAS Nodes: Call for Proposal #2

      ELIAS Nodes: Call for Proposal #2

      May 5, 2026 | ELIAS Alliance, Opportunities

      The ELIAS Alliance for European Leadership in Innovation with AI and Science has been established to strengthen academic and entrepreneurial education in the development of Frontier AI systems for European value creation. It combines Open Source model building with a novel innovation PhD track and a Europe-wide network of incubators, mentors, industry partners and startups. The AI Launchpad contributes to connecting AI researchers and startups with mentors and industry partners across Europe. In addition, the ELIAS Alliance recognizes outstanding frontier AI initiatives through an annual award presented at the ELIAS Frontier AI Summit (Copenhagen 2025, Stuttgart 2026). The ELIAS Alliance was launched in Nov 2024 with a first set of ELIAS Nodes (Amsterdam, Barcelona, Cambridge, Copenhagen, Munich, Potsdam, Tübingen, Zürich) and now calls for a 2nd round of proposals:

      Deadline to submit your proposals is

      July 5th, 2026

      Get in touch with the ELIAS Alliance Coordinator, Lisa Schöllhammer to receive access to the application form.

      GET IN TOUCH
      Application process

      The application for an ELIAS Node is focused on providing approved content for the ELIAS Node webpage covering the following points.


      1. Participating organizations, leadership, & Space
      • Text and pictures describing all organizations (e.g. higher-ed institutes, industry partners, funding bodies) supporting your ELIAS node and indicate how they support your node.
      • Provide a support letter from each organization signed by a C-level representative.
      • Commitment letter by each spokesperson(s) of the ELIAS node (one of them needs to be an ELLIS fellow). If you want to nominate multiple leads, specify who is committed to regularly participate at ELIAS Alliance meetings. 
      • Name the lead administrative coordinator responsible for communication between nodes across the ELIAS Alliance, and provide a support letter by the supervisor they are reporting to.
      • ELIAS Node Space: Text and pictures describing the physical address of the node and the amount of square meters available for coworking/lecturing space. Include pictures showing the space that demonstrate the physical visibility of the node.
      2. Vision & Academic education
      • Provide a concise summary of your vision for the node and the collaborative efforts with the other alliance partners.
      • ELIAS Alliance Innovation PhD: support letter from university
      • List of courses offered by the supporting institutions nurturing value creation and societal impact (specify if course credits count towards basic curricula)
      3. Team composition
      • ELIAS Node Members: List all members you want to include in the node (+ potential roles).
      • ELLIS Fellows: Provide text, picture, and quote for 3-10 (including the head of the node) ELLIS fellows summarizing their track record in innovation and entrepreneurship who can inspire and mentor students in academia to pursue an entrepreneurial career. The quote should say why and how they will engage with the ELIAS Node activities (including mentoring for the ELIAS/ELLIS innovation PhD, AI Launchpad).
      • Non-academic Advisors: Provide text, picture, and quote for 1-5 non-academic advisors summarizing their track record in innovation and entrepreneurship who can inspire and mentor students in academia to pursue an entrepreneurial career. The quote should say why and how they will engage with the ELIAS Node activities (including mentoring for the ELIAS/ELLIS innovation PhD, AI Launchpad).
      4. Entrepreneurial and Open Source AI Innovation activities
      • Most relevant FROntier AI projects (FROs/Startups/Open Source FMs): text and pictures featuring the 3 most impactful FROntier AI projects that are closely related to the ELIAS Node (ideally a member of the node is a key figure in the project); their projects are automatically nominated for the ELIAS Alliance FROntier AI Award.
      • Other key activities: text and pictures featuring other key activities of the ELIAS Node that are most relevant to nurture/advocate value creation and societal impact.
      • Describe your existing technology transfer ecosystem, including spin-offs, collaborations with startups, industry, and business schools, sciencepreneurial education and team-building efforts, and financial support for early-stage transfer projects.
      !
      5. Connection to ELLIS
      • ELIAS is part of the ELLIS initiative. Please describe your existing connection to the ELLIS/ELIAS community and how you plan to integrate the ELIAS node into this community effort.

        To receive access to the application form you are asked to get in touch with the ELIAS Alliance Coordinator, Lisa Schöllhammer (elias-coordination@tuebingen.ai)

        Guidelines for evaluation 

        Your proposal will be reviewed by a diverse team of international entrepreneurs and scholars based on your combined track record in entrepreneurship and AI research excellence and the level of commitment documented in your application, taking into account the following criteria:

        • ELIAS Nodes need to have a physical location, i.e. a well specified co-working space dedicated to entrepreneurial activities and agreement to support a joint co-branding. Attractive space with clear commitment to co-branding contributes to a strong application.
        • ELIAS Nodes have a convincing program for running sciencepreneurial courses in academia and support transfer projects. The application is strengthened if students can earn credit points for these courses, applicable towards their BSc/MSc/PhD degrees.
        • ELIAS Nodes are supporting and ideally participating in building open source foundation models. In particular, they offer an educational program that allows students to acquire hands-on experience with building large models. 
        • ELIAS Nodes partner with a business school and actively support team building with complementary skills (e.g. tech + business).
        • ELIAS Nodes have compelling collaborations with (a) startups and (b) industry. 
        • ELIAS Nodes are backed by ELLIS fellows and entrepreneurial mentors.
        • ELIAS Nodes are managed by a dedicated lead administrative coordinator ideally with experience in the coordination of entrepreneurial activities. 

        Have Questions?

        If you have any questions, please feel free to contact:

        elias-coordination@tuebingen.ai.

        Insights from TDW: Building the Foundations of Trustworthy AI

        Insights from TDW: Building the Foundations of Trustworthy AI

        May 4, 2026 | Events, TDW

        The rapid evolution of Artificial Intelligence continues to reshape our digital and physical landscapes. However, as AI systems grow in complexity and scale, so too does the need for rigorous frameworks to ensure they remain fair, secure, and sustainable. This critical need was the focal point of the recent TDW Trustworthy AI event, a major hybrid initiative hosted by Institut Polytechnique de Paris and  ENS – Department of Biology (IBENS), Paris, France and proudly co-organised by the ELIAS, ELLIOT, and ENFIELD European projects.

        By bringing together leading researchers and industry experts from across these powerhouse consortiums and hosting institutes, the event unpacked the critical challenges and emerging solutions in building AI we can genuinely rely on. Structured around three core pillars—Frugality, Fairness, and Trust—the workshop provided a comprehensive look into the future of responsible AI.

        Here are the key takeaways from the speaker sessions:

        Session 1: Frugality

        The opening session focused on resource-efficient AI and minimising the environmental footprint of large-scale deployments.

        Victor Charpenay (Associate Professor, École des Mines de Saint-Étienne / ENFIELD) kicked off the discussion by exploring the physical and systemic footprints of technology through Life Cycle Assessment (LCA). He highlighted a critical gap in current sustainability assessments: research is heavily biased towards measuring carbon emissions and evaluating “simple” AI models, largely overlooking the exponentially higher computational costs of modern generative AI. A vital concept he introduced was Technological Symbioses—instances where two technologies reinforce one another, amplifying their mutual impact. As AI integrates with sectors like concrete manufacturing, biochar synthesis, and data centre operations, understanding these symbiotic relationships is crucial for accurately assessing the higher-order environmental impacts of AI deployment.

        🔗View the slides

        Enzo Tartaglione (Full Professor, Télécom Paris, Institut Polytechnique de Paris / ELIAS) presented a fresh perspective on making deep neural networks more efficient. Rather than focusing on traditional pruning — removing individual weights or neurons — he argued that what actually matters for real-world speed gains is reducing the number of layers, since GPUs process layers sequentially regardless of their width. His talk introduced layer collapse as a principled compression tool: when a layer’s outputs become near-constant across inputs, that layer can simply be removed. He walked through a series of methods his group has developed to identify and induce this phenomenon, from entropy-based detection to regularisation-driven approaches, with results demonstrated across standard architectures and, more recently, large generative models.

        🔗View Slides

        Session 2: Fairness

        The second session addressed algorithmic bias, socio-technical alignment, and how to ensure AI systems prevent discrimination in real-world applications.

        Ruta Binkyte-Sadauskiene (Researcher, CISPA / ELLIOT) emphasised the urgent need to rethink fairness as AI evolves from basic prediction models to Large Language Models (LLMs) and Agentic AI. She detailed how the nature of bias shifts along this spectrum: traditional machine learning is plagued by prediction bias, generative AI introduces severe stereotyping and toxicity, and autonomous AI agents lead to deceptive behavior, collusion, and emergent misalignment.  She proposed interactional fairness—a framework adapted from organisational psychology (Greenberg, 1987) to LLM multi-agent systems—to evaluate and measure how informational (justification quality) and interpersonal (tone) dimensions affect agent cooperation. To demonstrate this, she shared a multi-agent disaster relief scenario where coordination stalled when an agent demanded 70% of resources without explanation, but succeeded once a triage-based justification was provided. This research highlights that as agents interact with humans and one another, biases compound in complex, unpredictable ways that require entirely new frameworks for detection, measurement and mitigation.

        🔗View Slides

        Charlotte Laclau (Associate Professor, Télécom Paris, IP Paris / ELIAS) began by emphasising that fairness cannot be treated as a simple “plug-in” constraint that is easily transferred across different learning settings. She argued that a meaningful notion of fairness must be defined relative to three core elements: the object being predicted, the intervention point, and the data-generating system. Highlighting challenges in “Fair Link Prediction,” she noted that natural human mechanisms like homophily—the tendency to associate with similar individuals—can create systemic segregation in online networks. Consequently, mitigating these biases requires topological awareness, such as evaluating “k-hop fairness,” rather than relying on surface-level metrics. Laclau noted that the critical question for developers is no longer “Which metric is best?” but rather “Which notion matches the system and the specific harm we aim to prevent?

        🔗View Slides

        Session 3: Trust

        The final session centred on enhancing the robustness, security, and integrity of AI, particularly in high-stakes cloud environments and human-AI interactions.

        Sebastian Heil (Senior Researcher, Chemnitz University of Technology / ENFIELD) explored the crucial dimension of Human Perception of AI Trustworthiness. Drawing on a longitudinal study of UK news media spanning from 2013 to 2024, Heil illustrated that public discourse around AI is maturing. The conversation is actively shifting away from the blind celebration of technical achievements towards critical expectations of transparency and accountability. To measure how users actually build trust with AI, he detailed ongoing vignette-based survey research across critical domains. This research isolates specific system characteristics—such as the presence of active human oversight or technical fallback mechanisms—to understand exactly what drives user confidence. Quoting Kevin Kelly, Heil emphasised that trust is “earned in drops and lost in buckets,” underscoring the need for systems that demonstrably align with the core requirements of the EU’s Ethics Guidelines for Trustworthy AI.

        🔗View Slides

        Georgios Spathoulas (NTNU / ENFIELD) closed the technical sessions by discussing the rise of AI as a Service (AIaaS) and the resulting “black box” problem, where users cannot see or verify the models behind API-based AI systems, creating a major trust gap.

        He outlined three key vulnerabilities: possible hidden model substitution by providers, lack of transparency in training data integrity, and performance drift from continuous fine-tuning.

        To address these issues,  Spathoulas recalled for a paradigm shift from blind trust to cryptographic verification. He detailed a robust blend of technical safeguards—such as cryptographic model provenance, digital watermarking, and Trusted Execution Environments (TEEs) like Intel SGX and ARM TrustZone—as well as organisational governance frameworks like transparency policies and independent auditing. Notably, he highlighted Zero-Knowledge Proofs (ZKPs) as a revolutionary way to verify computational integrity, allowing providers to prove a specific model was used without exposing proprietary parameters or sensitive client data.

        🔗View Slides

        The Path Forward

        The TDW Trustworthy AI event made one thing abundantly clear: building reliable AI is a multidisciplinary challenge requiring immediate, coordinated action. The co-organisation of this event by the ELIAS, ELLIOT, and ENFIELD projects—supported by the hosting institutes in Paris—exemplifies exactly the kind of cross-institutional, collaborative effort needed to drive this field forward. From contextualising interactional fairness and cryptographically securing cloud models to measuring the psychological foundations of user trust and physical environmental impacts, the ecosystem is recognising that integrity and frugality are no longer optional. They are the fundamental prerequisites for the future of AI in Europe and beyond.

        Watch the event recording here!

        This TDW marked the third in a series of thematic workshops organised by ELIAS, in collaboration with the ELLIOT and ENFIELD networks.

        Check out the previous editions: Theme Development Workshops

        ELLIOT – European Large Open Multi-Modal Foundation Models For Robust Generalization On Arbitrary Data Streams (GA No. 101214398 ) aims to develop the next generation of open Multimodal Generalist Foundation Models (MGFMs): AI systems designed to learn general knowledge and patterns from massive amounts of data of various types — from videos, images, and text to sensor signals, industrial time series, and satellite feeds — and efficiently transfer the generic knowledge learned in generalist manner to a wide variety of downstream tasks. Unlike current foundation models that face significant challenges in terms of generalisation capabilities and support for multimodal data, ELLIOT’s models will be capable of robust generalisation across conditions not seen during the training, coping well with dynamic, noisy, and temporally-evolving multimodal data streams. Real and synthetic data will be leveraged for training MGFMs and for further adapting them for specific downstream tasks in domains like media, earth observation, robot perception, mobility, computer engineering and workflow automation. European HPC infrastructure is directly included in the consortium to ensure the availability of the necessary computing resources. www.elliot-ai.eu

        ENFIELD – European Lighthouse to Manifest Trustworthy and Green AI (GA No. 101120657) aims to advance adaptive, green, human-centric and trustworthy AI by establishing a European Centre of Excellence. With a consortium of 30 partners from 18 countries—covering academia, industry, SMEs and the public sector—the project targets key domains such as healthcare, energy, manufacturing and space. ENFIELD will deliver over 75 AI solutions, around 180 high-impact publications, and strategic roadmaps, supported by extensive outreach to foster responsible AI adoption across Europe. www.enfield-project.eu

        Responsible AI in Focus: ELIAS and IRCAI at GITEX AI Asia in Singapore

        Responsible AI in Focus: ELIAS and IRCAI at GITEX AI Asia in Singapore

        Apr 22, 2026 | Events, News

        SINGAPORE — At GITEX AI ASIA, recognised as Asia’s largest and most global tech, AI, and startup event, the IRCAI, International Research Centre on Artificial Intelligence under the auspices of UNESCO, alongside the European Lighthouse of AI for Sustainability (ELIAS), took centre stage to advance the global dialogue on ethical artificial intelligence.

        The event took place in Singapore from April 9–10, 2026. Joao Pita Costa represented the work of both IRCAI and ELIAS. Engaging a diverse audience of policymakers, researchers, innovators, and entrepreneurs, he led sessions exploring the collaborative design and deployment of AI systems that are powerful, inclusive, and aligned with societal values.

        Equipping Practitioners: A Hands-On ELIAS Tutorial on Responsible AI

        A major highlight of the programming was the hands-on ELIAS tutorial titled, “Building Responsible AI Ecosystems: From Theory to Action for Public Good.”. The session equipped participants with practical tools to embed ethics directly into AI development.

        Moving away from the importation of external, centralised models, the tutorial focused on empowering local actors—citizens, researchers, startups, and regulators—to co-create AI solutions using data they can access, govern, and trust. Participants explored practical approaches to:

        • Adapting Responsible AI Principles: Tailoring fairness, transparency, and accountability to low-resource and edge environments.

        • Leveraging Frugal Edge AI: Creating affordable, energy-efficient, and offline-capable AI systems uniquely suited for Asian contexts.

        • Empowering Communities: Utilising participatory citizen science for data contribution and problem definition while guaranteeing data sovereignty and local ownership.

        • Governance and Regulation: Utilising sandboxes and community-centric frameworks to foster technological experimentation while strictly protecting the public interest.

        View the slides

        Accelerating Impact: The Main Stage Panel

        An important discussion continued on the Main Stage  on April 9 with the highly anticipated panel, “Responsible AI in Action: Accelerate AI for Public Good in Asia.” Moderated by Joao Pita Costa, the panel convened a dynamic group of regional leaders to discuss scaling inclusive, human-centered AI across the continent.

        The distinguished panel of experts included:

        • Hammam Riza, KORIKA (Indonesia)

        • William Tjhi, AI Singapore, SEA LION LLM (Singapore)

        • Chalitda Madhyamapurush, Thailand AI Governance Centre (Thailand)

        • Jyoti Rahaman, Asian-European Foundation (ASEF) (Singapore)

        From Pilots to Real-World Impact

        The cross-sector energy in Singapore underscored a vital truth: transitioning from AI pilots to massive societal impact requires more than just technology. It demands trusted partnerships, local relevance, and an unwavering commitment to ethical AI.

        ELIAS and IRCAI extend their gratitude to all partners, participants, and GITEX Asia for creating a dynamic space where global ambition meets regional action. The future of AI must be shaped collectively, and responsibly.

        ELIAS Open Call for SMEs, Startups & NGOs

        ELIAS Open Call for SMEs, Startups & NGOs

        Feb 27, 2026 | ELIAS Alliance, Opportunities

        ELIAS Open Call

        Overview

        A focused opportunity to connect applied innovation with cutting‑edge research on sustainable and trustworthy AI.
        • Contribute to energy‑efficient and resource‑aware AI methods and tools.
        • Strengthen trustworthiness, transparency, and robustness of AI systems.
        • Provide benchmarks, datasets, or evaluation frameworks for sustainable AI.
        • Demonstrate real‑world impact in societal, environmental, or public‑sector contexts.
        Sustainable AI Trustworthy AI Benchmarks & Evaluation Applied Use Cases

        Who can apply

        The call is open to legal entities established in eligible countries, with a clear focus on applied innovation.

        Eligible applicants

        • Small and medium‑sized enterprises (SMEs).
        • Startups and spin‑offs.
        • Non‑governmental and non‑profit organisations (NGOs, foundations, associations).

        Conditions

        • The organisation is legally established in an EU Member State or associated country.
        • The proposed work is aligned with the scope and objectives of the ELIAS project.
        • The applicant can demonstrate the capacity to implement the proposed activities within the funding period.
        Detailed eligibility rules are provided in the Giudelines.

        What we fund

        We support focused projects that extend, validate, or apply ELIAS research in real‑world contexts.

        Funding pillars

        • Methods & Algorithms
          Novel approaches for energy‑efficient AI, trustworthy learning, foundation models with reduced footprint, or methods that improve transparency and robustness.
        • Software & Tools
          Open‑source toolkits, benchmarks, datasets, or evaluation frameworks that support sustainable and responsible AI development and deployment.
        • Applied Use Cases
          Solutions that apply ELIAS‑relevant methods to domains such as climate action, public services, mobility, or social inclusion.

        Funding and duration

        €60,000
        Max financial support
        6 months
        Expected duration
        The exact funding amount will depend on the scope, ambition, and expected impact of the proposal.

        Timeline

        Key milestones from call opening to project start, to help you plan your proposal and activities.

        Call opens
        27 February 2026

        Publication of the call text, templates, and Guidelines for Applicants.

        Info session
        1 April 2026

        Online webinar to present the call and answer questions from potential applicants.

        Submission deadline
        31 May 2026

        Proposals must be submitted by 23:59 CET via the online application form.

        Evaluation & results
        July–September 2026

        Evaluation, selection, and communication of results. Projects are expected to start in Q4 2026.

        Evaluation criteria

        Proposals will be evaluated by independent experts based on excellence, impact, and quality of implementation.

        Excellence

        Clarity of objectives, soundness of the concept, and degree of innovation. Alignment with ELIAS research topics and state‑of‑the‑art methods in sustainable and trustworthy AI.

        Impact

        Potential to generate measurable benefits for users, communities, or sectors. Contribution to European leadership in responsible AI and to the long‑term sustainability of ELIAS outcomes.

        Implementation

        Quality and feasibility of the work plan, adequacy of resources, and capacity of the team to deliver the proposed results within time and budget.

        Detailed scoring guidelines and thresholds are provided in the Guidelines for Applicants.

        How to apply

        A simple, step‑by‑step process to prepare and submit your proposal.

        Step 1
        Read the call documents

        Download and carefully read the Call text and Guidelines for Applicants to confirm your eligibility and fit.

        Step 2
        Prepare your proposal

        Describe your objectives, methodology, impact, and work plan.

        Step 3
        Submit online

        Complete the online application form and upload your proposal before the deadline.

        Ready to submit your idea?
        Go to application form

        Proposals submitted after the deadline will not be considered eligible.

        Resources

        All documents you need to prepare a complete and competitive proposal.

        Guidelines for Applicants Practical guidance on how to prepare and submit your proposal. Download
        Q&A Session Presentation Slides from the information session, including key explanations and answers to participants’ questions. View presentation
        FAQ Answers to frequently asked questions about the call and evaluation process. View FAQ
        Open Call Official Documents Includes all mandatory documents:
        • Document 1 – Open Call Project Description
        • Document 2 – Type of Organization
        • Document 3 – Specific Obligations under Grant Agreement
        • Document 4 – Background IP
        • Document 5 – Budget Template         Download
        #

        Contact

        We encourage you to reach out early if you have questions about eligibility or scope.

        Questions on eligibility, scope, or submission process