Call for Papers

The ICE 2026 Organising Committee invites high quality papers to be presented at this premier international event. Submissions should contribute to a substantial, original and previously unpublished research in the topics of the conference:

  • Industry 5.0
    • Advanced Service Systems and Automation
    • AI-Driven Manufacturing and Production
    • Intelligent,Adaptive and resilient Supply Chains
    • Smart Manufacturing and Autonomous Systems
    • Smart Production and Process Optimization
    • Smart Services and Customer-Centric Solutions
  • Sustainable Engineering & Circular Manufacturing
    • Carbon-Neutral and Renewable Energy Manufacturing
    • Circular and Closed-Loop Manufacturing Systems
    • Eco-friendly and Low-Impact Production Technologies
    • Green and Sustainable Supply Chains
    • Resource-efficient and Optimized Systems
    • Zero-waste and Sustainable Production Models
    • Human Centred Production Systems
  • Digital Technologies
    • Artificial Intelligence and Autonomous Systems
    • Advanced Cybersecurity and Threat Intelligence
    • Digital Health Technologies
    • Internet of Things and Edge Computing
    • Machine Learning and Deep Learning Applications
    • Smart Systems and Autonomous Infrastructure
  • Digital Transformation
    • Agile Organizational Transformation Strategies
    • AI-Enhanced Data-Driven Decision Making
    • Evolving Role of CIO/CDO in Innovation and Strategy
    • Holistic Transformation and Change Management
    • Leadership in the Age of Digital Transformation
    • Seamless Integration of Legacy Systems
  • Open Innovation and Collaboration
    • Collaborative Experience Design and Innovation
    • Crowdsourced and Co-Created Innovation
    • Circular and Sustainable Innovation Models
    • Living Labs and User-Driven Innovation
    • Networked and Cross-Industry Innovation
    • Responsible and Ethical Innovation Practices
    • User Driven Innovation and Living Labs
    • Purpose-driven innovation and business
  • Innovation Ecosystems and Responsibility
    • Inclusiveness and Accessible Innovation
    • Resilient Societies through Inclusive Innovation
    • Social Innovation for Community Development
    • Societal Resilience and Adaptive Innovation
    • Sustainable and Eco-Driven Innovation
    • Technological Innovation for Global Challenges
    • Education for Sustainable Innovation
    • Teaching and Learning Collaborative Environments
    • Public-Private Collaboration
  • Entrepreneurial Ecosystems and Support
    • Collaborative Networks in Entrepreneurship
    • Digital and Platform-Based Entrepreneurship
    • Entrepreneurship and Venture Growth Metrics
    • Entrepreneurship in Developing and Emerging Economies
    • Female-Led and Gender-Inclusive Entrepreneurship
    • Social Entrepreneurship and Sustainable Business Models
    • Commercialization Strategies for Technological Innovations
  • Corporate Entrepreneurship and Intrapreneurship
    • Ambidextrous Leadership for Innovation and Efficiency
    • Corporate Venturing and Innovation Investment
    • Organizational Ambidexterity in Dynamic Markets
    • Strategic and Organizational Renewal Initiatives
    • Support Structures and Processes

The topics of interest are examples, other topics that fit into the areas of the conference are welcome.

  • ENG 1: Industry 5.0 and Smart Manufacturing
    • AI-driven production, automation, and robotics
    • Adaptive and resilient supply chains
    • Smart systems for process optimisation
    • Human-centred and service-oriented production
  • ENG 2: Sustainable and Circular Engineering
    • Carbon-neutral and renewable energy manufacturing
    • Circular Engineering and closed-loop production systems
    • Eco-friendly and low-impact materials and processes
    • Resource efficiency and zero-waste models
  • ENG 3: Industrial Decarbonisation and Energy Systems
    • Electrification of energy-intensive industries
    • Integration of hydrogen, renewables, and smart grids
    • AI and IoT for energy optimisation and monitoring
    • Health and environmental impact tracking through digital tools
  • ENG 4: Resilience, Preparedness, and System Supervision
    • Monitoring and diagnostics in complex industrial systems
    • Readiness assessment and operational resilience
    • Supervisory control for adaptive and autonomous systems
    • Crisis detection, response, and recovery mechanisms
  • ENG 5: Bioeconomy and Industrial Biotechnology
    • Bio-based innovation for decarbonisation and circularity
    • Biomanufacturing platforms and synthetic biology
    • Sustainable production of biomaterials and biofuels
    • Integration of biotechnology in low-impact production
  • TEC 1: Artificial Intelligence for Technology Management
    • Generative AI for Technology Management in the context of Industrial and Educational Intelligence
    • AI-supported technology and innovation strategy, portfolio management, and roadmapping
    • AI-enabled decision support for R&D, operations, and product–service systems
    • Organizational capabilities, governance, skills for AI in technology and engineering management
    • AI-driven business model innovation, value creation, and ecosystem development
    • Human-centered, trustworthy, and responsible AI for technology management (including implications of the EU AI Act)
    • Case studies and lessons learned from deploying AI in industrial and educational contexts
  • TEC 2: Digital Transformation for Competitiveness
    • Digital Transformation Case Studies, Best Practices & Managerial Insights
    • Digital Transformation Challenges, Benefits & Drawbacks
    • Digital Transformation GenAI LLM versus SLM
    • Digital Transformation Strategies, Leadership and Management
    • AI/ML in industrial processes and supply chains
    • Quantum computing, 6G, and next-gen networks in manufacturing
    • Industrial digital twins and real-time simulation tools
    • Leveraging Metaverse for Digital Transformation
  • TEC 3: Data Spaces and Digital Product Transparency
    • Digital Product Passports for circular economy and traceability
    • Federated and secure industrial data spaces
    • Blockchain and IoT for trusted product data
    • Standardisation, governance, and interoperability frameworks
  • TEC 4: Generative AI and Human-in-the-Loop Innovation
    • AI-assisted industrial and educational design and decision-making
    • Creative and ethical use of generative AI under EU AI Act
    • Human-in-the-loop systems and explainability in high-stakes contexts
    • AI for R&D, industrial training, and continuous learning
    • Health, Climate, and Industrial Resilience
  • TEC 5: Climate adaptation in healthcare and industrial systems
    • Digital tools for monitoring health and environmental change
    • Low-carbon and climate-resilient supply chains
    • Preparedness and resilience in critical infrastructure
  • INN 1: Open and Collaborative Innovation
    • Co-creation, crowdsourcing, and living labs
    • Networked and cross-industry collaboration
    • User-driven and purpose-oriented innovation
    • Circular and sustainable innovation models
    • User Experience
    • Open Innovation
    • User Centric Innovation
    • Experience Design
    • Design Thinking
  • INN 2: Innovation Ecosystems and Responsibility
    • Inclusive and accessible innovation practices
    • Education and skills for sustainable innovation
    • Social innovation and community resilience
    • Ethical and responsible innovation governance
  • INN 3: Policy, Regulation, and Standards
    • Technology-neutral innovation policy frameworks
    • Public–private partnerships and clean tech scale-up
    • EU-level coordination and standardisation (AI, cybersecurity, carbon)
    • Governance mechanisms for responsible innovation
  • INN 4: Skills, People, and Societal Transition
    • Workforce transformation for green and digital jobs
    • Engineering and entrepreneurial education for twin transitions
    • Human-centric AI and inclusive innovation ecosystems
    • ILifelong learning and adaptive capacity building
  • INN 5: Smart Cities, Living Labs, Democratizing Innovation and Citizen Engagement
    • User-Driven Innovation, eXperience Design, Living-Labs and Smart-Cities Experimentation
    • User-Engagement, Do-It-Yourself (DIY) and Do-It-Together (DIT) experimentation in the context of Social Media and Digital Transformation
    • Participatory innovation models and citizen co-design in urban transitions
    • Open and inclusive governance frameworks for industrial and technological policy
    • Citizen science and community-driven experimentation in climate and digital innovation
    • Social innovation labs and local ecosystems supporting green entrepreneurship
    • Urban Intelligence towards Citizens Assemblies as a methodology for promoting citizens as active agents in the co-creation of solutions and interventions in cities.
  • ENT 1: Entrepreneurial Ecosystems and Support
    • Collaborative networks and support infrastructures
    • Digital, platform-based, and data-driven entrepreneurship
    • Inclusive and sustainable business models
    • Commercialisation and growth strategies in emerging markets
  • ENT 2: Corporate Entrepreneurship and Intrapreneurship
    • Ambidexterity and organisational renewal
    • Corporate venturing and internal venture building
    • Bottom-up innovation and employee-led initiatives
    • Structures and processes for entrepreneurial culture
  • ENT 3: Social and Sustainable Entrepreneurship
    • Mission-driven ventures addressing societal challenges
    • Circular and green business models
    • Social value creation and local ecosystem engagement
    • Gender-inclusive and diversity-focused entrepreneurship
  • ENT 4: Scaling and Impact in Clean and Digital Sectors
    • Start-up and SME transition pathways in clean tech
    • Public–private partnerships and funding for impact ventures
    • Global market integration and competitiveness
    • Metrics for entrepreneurial growth and sustainability

ENGINEERING

  • ENG 1: Industry 5.0 and Smart Manufacturing
    • AI-driven production, automation, and robotics
    • Adaptive and resilient supply chains
    • Smart systems for process optimisation
    • Human-centred and service-oriented production
  • ENG 2: Sustainable and Circular Engineering
    • Carbon-neutral and renewable energy manufacturing
    • Circular Engineering and closed-loop production systems
    • Eco-friendly and low-impact materials and processes
    • Resource efficiency and zero-waste models
  • ENG 3: Industrial Decarbonisation and Energy Systems
    • Electrification of energy-intensive industries
    • Integration of hydrogen, renewables, and smart grids
    • AI and IoT for energy optimisation and monitoring
    • Health and environmental impact tracking through digital tools
  • ENG 4: Resilience, Preparedness, and System Supervision
    • Monitoring and diagnostics in complex industrial systems
    • Readiness assessment and operational resilience
    • Supervisory control for adaptive and autonomous systems
    • Crisis detection, response, and recovery mechanisms
  • ENG 5: Bioeconomy and Industrial Biotechnology
    • Bio-based innovation for decarbonisation and circularity
    • Biomanufacturing platforms and synthetic biology
    • Sustainable production of biomaterials and biofuels
    • Integration of biotechnology in low-impact production


TECHNOLOGY

  • TEC 1: Artificial Intelligence for Technology Management
    • Generative AI for Technology Management in the context of Industrial and Educational Intelligence
    • AI-supported technology and innovation strategy, portfolio management, and roadmapping
    • AI-enabled decision support for R&D, operations, and product–service systems
    • Organizational capabilities, governance, skills for AI in technology and engineering management
    • AI-driven business model innovation, value creation, and ecosystem development
    • Human-centered, trustworthy, and responsible AI for technology management (including implications of the EU AI Act)
    • Case studies and lessons learned from deploying AI in industrial and educational contexts
  • TEC 2: Digital Transformation for Competitiveness
    • Digital Transformation Case Studies, Best Practices & Managerial Insights
    • Digital Transformation Challenges, Benefits & Drawbacks
    • Digital Transformation GenAI LLM versus SLM
    • Digital Transformation Strategies, Leadership and Management
    • AI/ML in industrial processes and supply chains
    • Quantum computing, 6G, and next-gen networks in manufacturing
    • Industrial digital twins and real-time simulation tools
    • Leveraging Metaverse for Digital Transformation
  • TEC 3: Data Spaces and Digital Product Transparency
    • Digital Product Passports for circular economy and traceability
    • Federated and secure industrial data spaces
    • Blockchain and IoT for trusted product data
    • Standardisation, governance, and interoperability frameworks
  • TEC 4: Generative AI and Human-in-the-Loop Innovation
    • AI-assisted industrial and educational design and decision-making
    • Creative and ethical use of generative AI under EU AI Act
    • Human-in-the-loop systems and explainability in high-stakes contexts
    • AI for R&D, industrial training, and continuous learning
    • Health, Climate, and Industrial Resilience
  • TEC 5: Climate adaptation in healthcare and industrial systems
    • Digital tools for monitoring health and environmental change
    • Low-carbon and climate-resilient supply chains
    • Preparedness and resilience in critical infrastructure


INNOVATION

  • INN 1: Open and Collaborative Innovation
    • Co-creation, crowdsourcing, and living labs
    • Networked and cross-industry collaboration
    • User-driven and purpose-oriented innovation
    • Circular and sustainable innovation models
    • User Experience
    • Open Innovation
    • User Centric Innovation
    • Experience Design
    • Design Thinking
  • INN 2: Innovation Ecosystems and Responsibility
    • Inclusive and accessible innovation practices
    • Education and skills for sustainable innovation
    • Social innovation and community resilience
    • Ethical and responsible innovation governance
  • INN 3: Policy, Regulation, and Standards
    • Technology-neutral innovation policy frameworks
    • Public–private partnerships and clean tech scale-up
    • EU-level coordination and standardisation (AI, cybersecurity, carbon)
    • Governance mechanisms for responsible innovation
  • INN 4: Skills, People, and Societal Transition
    • Workforce transformation for green and digital jobs
    • Engineering and entrepreneurial education for twin transitions
    • Human-centric AI and inclusive innovation ecosystems
    • ILifelong learning and adaptive capacity building
  • INN 5: Smart Cities, Living Labs, Democratizing Innovation and Citizen Engagement
    • User-Driven Innovation, eXperience Design, Living-Labs and Smart-Cities Experimentation
    • User-Engagement, Do-It-Yourself (DIY) and Do-It-Together (DIT) experimentation in the context of Social Media and Digital Transformation
    • Participatory innovation models and citizen co-design in urban transitions
    • Open and inclusive governance frameworks for industrial and technological policy
    • Citizen science and community-driven experimentation in climate and digital innovation
    • Social innovation labs and local ecosystems supporting green entrepreneurship
    • Urban Intelligence towards Citizens Assemblies as a methodology for promoting citizens as active agents in the co-creation of solutions and interventions in cities.


ENTREPRENEURSHIP

  • ENT 1: Entrepreneurial Ecosystems and Support
    • Collaborative networks and support infrastructures
    • Digital, platform-based, and data-driven entrepreneurship
    • Inclusive and sustainable business models
    • Commercialisation and growth strategies in emerging markets
  • ENT 2: Corporate Entrepreneurship and Intrapreneurship
    • Ambidexterity and organisational renewal
    • Corporate venturing and internal venture building
    • Bottom-up innovation and employee-led initiatives
    • Structures and processes for entrepreneurial culture
  • ENT 3: Social and Sustainable Entrepreneurship
    • Mission-driven ventures addressing societal challenges
    • Circular and green business models
    • Social value creation and local ecosystem engagement
    • Gender-inclusive and diversity-focused entrepreneurship
  • ENT 4: Scaling and Impact in Clean and Digital Sectors
    • Start-up and SME transition pathways in clean tech
    • Public–private partnerships and funding for impact ventures
    • Global market integration and competitiveness
    • Metrics for entrepreneurial growth and sustainability

Important Dates

ICE IEEE/ITMC

27 Feb 2026 03 April 2026: Full Paper Submission
24 May 2026: Author Notification
29 May 2026: Camera-ready version
22-24 June 2026: ICE Conference


This includes, but is not limited to:

  • Theoretical research papers that provide new concepts in the domain of engineering, technology, and innovation;
  • Empirical studies and qualitative case studies that develop new insights;
  • System design and development papers that go beyond the pure description of systems and give insight into theory and effectiveness of the approach;
  • Verification and validation papers that evaluate the application of solutions.

The review committee is available to provide feedback on paper ideas.

For any questions, please contact the secretariat at info@ice-conference.org.

Call Special Tracks and Special Sessions 

Special Tracks at ICE 2026 provide a focused forum on strategic and emerging topics, bringing together research, innovation, and expert perspectives within a coherent thematic framework. Each Special Track is coordinated by a dedicated committee of chairs and typically combines scientific paper sessions, interactive workshops, and an expert panel discussion. This integrated format encourages in-depth technical exchange, community building, and dialogue between academia, industry, and policy, fostering both scientific excellence and practical impact around the selected topic.

Chairs
Chair: 
Sudip Chakarborty, IEEE TEMS, sudip.chakarborty@unical.it
Co-Chair: 
Eduardo Ahumada-Tello, IEEE TEMS, eahumada@ieee.org | Robert Bierwolf, ICE Community, robert.bierwolf@xs4all.nl
Important Dates
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
Description
The Technology Management (TM) concept and “AI for TM” Within Science Direct Social Sciences (SDSS, 2025)Technology Management” is defined by AI generated definition based on [Reference Module in Social Sciences, 2024] “as the strategic alignment of technology with organizational goals, fostering innovation, and navigating the complexities of the technological landscape to achieve sustainable success. It involves embracing recent trends and best practices, such as agile development and data analytics, to drive organizational success in the digital era.” It is well admitted that Technology Management is composed of different activities, such as planning, design, optimization, operation and control of technological products, and related processes as well as services. It includes several disciplines, namely: strategy, forecasting, road mapping, portfolio and transfer that allow any organization to manage whatever technology implementation leading to an increase of competitiveness. The TM concept includes technology strategy, forecasting, scouting, road mapping, and transfer. White & Bruton (2010) define TM as a management process to plan, develop, implement, monitor, and control technological capabilities contributing to fulfill the organization goals. Gajda et al. (2025), argue that “AI-based innovation management has developed into a rapidly expanding and influential research field, moving from marginal attention in the early 2000s to a mainstream domain after 2018. The field integrates technological, managerial, and societal perspectives, with themes ranging from generative AI and decision support to sustainability, open innovation, and organizational change. Research confirms that AI functions both as a practical tool for improving processes and as a transformative force redefining knowledge creation and foresight. Overall, AI-based innovation management has matured into a cornerstone of digital transformation, offering both theoretical advances and practical tools for organizations seeking sustainable competitiveness in the knowledge economy.” According to Corvello (2025), innovation managers “face similar challenges when it comes to appropriating GenAI for product development and R&D processes. A study by Cimino et al. (2024) found that innovation managers in the automotive industry are using GenAI to simulate new vehicle designs and test prototypes in virtual environments. This allows firms to identify potential design flaws before building physical prototypes, reducing costs and speeding up the innovation process. However, as with project managers, the level of appropriation varies significantly depending on the individual’s expertise and the organization’s culture.” Bilgram and Laarmann (2023) argue that generative artificial intelligence (GenAI) allows to democratize the use of AI in innovation management and consequently change both work and innovation approaches. Their experimentation with LLMs in the early phases of innovation and prototyping revealed the following three major insights: (1) there is a plethora of use cases ranging from user journey mapping to idea generation and prototyping where LLMs can support users on how to complete, for example, methodological support for designing an interview guideline and apply knowledge to perform tasks like answering questions for needs along the user journey. Authors foresee a promising role LLMs may play in future knowledge management systems based on LLMs tapping external sources. (2) GenAI, through the use of artificial agents, could become a game changer in early prototyping resulting in faster iterations and reduced costs as well as allowing users getting competencies in new fields and prototype functionalities. Authors foresee a potentially rapid progress in the emergence of specialized AI design tools for high quality design prototyping replacing the manual digital one in early phases. (3) authors experiences show that LLMs imply to reconsider the way innovation teams purposively and effectively interact with AIs and their integration into their workflows. They argue also that involved managers pointed out that “AI-generated information often resembles a draft version created by a skilled human assistant”. They found that this approach is easier and less time-consuming for editing a version than producing initial thoughts. Overall, authors argue that innovation methods, like design thinking, need to be reconsidered in order to seize these above-mentioned GenAI opportunities. Brem et al. (2023) discuss the diverse ways AI is transforming innovation. They present a conceptual framework in which they argue AI plays the following two roles: originator and facilitator of innovation. They also discuss different applications and implications for innovation theory and practice using a reflection on the traditional innovation process and the Front-End of Innovation (FEI) perspective. For this, authors use the perspectives of AI as technology push, AI as market pull, AI to advance steps in the innovation funnel as well as AI as a contributor to New Product Development (NPD). Authors provide (Fig. 1) a final overview of their introduced view of AI as an originator and a facilitator. These perspectives can be linked to key areas/research questions in innovation research. Cooper (2024) proposed an exploratory journey through a mapping exercise crossing the role of AI alongside the innovation funnel stages, starting from the Front-End of Innovation (FEI) to the Back-End of Innovation (BEI) including the postlaunch period. He rightly points out that AI in New Product Development (NPD) was initiated, in fact expert systems, in the late 1970s and early 1980s allowing to automatize complex stage-gates processes mimicking decision-making capabilities of human experts. It happens simultaneously with the Computer-Aided Design & Computer-Aided Manufacturing (CAD/CAM) revolution in the NPD process. It is worth mentioning that apart the technology-based evolution of NPD, new methodological approaches, like System Engineering, Concurrent Engineering, and Circular Engineering have also revolutionized the entire NPD process. Cooper relates that a search for existing AI apps reveals lot of them within the NPD process from FEI idea generation to BEI product launch. He proposes a mapping between AI apps/role and NDP stages (fig. 2) for clarifying their roles, timing, location, and nature in order to better understand this complex AI-NPD landscape According to Cooper and Brem (2024), AI adoption in NPD remains particularly low in the FEI as shown by a study revealing that AI use across five predevelopment activities averaged just 6% while 78% of firms are not using AI for any of these FFE tasks. Cooper (2025) explores the Fuzzy Front-End (FFE) of the NPD process where AI creates new product ideas while comparing all of them according to a set of specified criteria allowing AI to prioritize the best ideas. He provides examples of AI for ideation and screening ideas that reveal positive results through the automation of repetitive tasks quickly leading to valuable insights, hence, more accurate decisions. He also demonstrates, based on provided examples, that AI can also conduct market and competitive analysis while assisting in market research and customer feedback, reducing costs as well as accelerating development timelines with higher NPD success rates. According to Mubarak et al. (2025), strategic leadership, cross-functional collaboration, and a commitment to continuous learning allow to deliver the full potential of AI implementation in the NPD process. Furthermore, authors argue that talent acquisition, ethical and legal concerns, and organizational resistance remain challenges to overcome by proactive management and investment in AI for ensuring a long-term success. Nonetheless, authors mention the following managerial implications: (1) setting-up a necessary NPD governance framework for responsible and ethical use of AI; (2) conform to regulatory requirements regarding data privacy and security like the recent EU AI Act, which is the first legal framework and regulation on AI ensuring that firms develop and use human-centric and trustworthy AI systems; (3) launch specific change management and stakeholder engagement strategies including a necessary cultural shift toward embracing data-driven decision-making for ensuring a successful AI implementation within the NPD process for remaining competitive (Palzer, 2022).
Review Committee
Chairs
Chair: 
Luca Canetta, IEEE TEMS (luca.canetta@supsi.ch)
Co-Chair: 
Ricardo Jardim Gonçalves, ICE Community (rg@uninova.pt) | Gerhard Gudergan, ICE Community (Gerhard.Gudergan@fir.rwth-aachen.de)
Important Dates
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
Description
The Digital Transformation Concept
It is widely admitted that Digital Transformation (DT) impacts our entire society especially through the Digital Economy (DE) and in particular all business sectors. In fact, all entities, either public or private, Large or Small and Medium-sized Enterprises (SMEs) as well as individuals have the opportunity to innovate their value proposition while dramatically improving their operative mode in applying digital technologies. Nowadays, well-known technologies, such as: Mobile, Social-Networks (SN), Big-Data (BD), Artificial Intelligence (AI), Internet of Things (IoT), eXtended Reality (XR), Additive Manufacturing (AM), just to cite a few, have demonstrated their capacity to improve operative factors like, for example, increased effectiveness, efficiency, reliability and replicability of operational processes. Recently, scholars like Gong & Ribiere (2021) argued that existing literature demonstrates evidence of lacking a universal and comprehensive understanding of the DT concept leads to a misunderstanding of the essence of this phenomenon. Consequently, they attempted to formalize a unified definition of DT as follow: “A fundamental change process, enabled by the innovative use of digital technologies accompanied by the strategic leverage of key resources and capabilities, aiming to radically improve an entity* and redefine its value proposition for its stakeholders.” (* An entity could be: an organization, a business network, an industry, or society).

The Twin Transition Concept
In recent years, digital transformation has gained even greater importance than before. It is regarded as a key enabler for fundamentally restructuring supply chains and the associated digital ecosystems; especially since the European Union new Digital Product Passport (DPP) regulation. This transformation aims to increase resilience and facilitate the traceability of life-cycle data towards a transition on circular material and product cycles. In this context, digitalization and the circular economy are increasingly seen as two sides of the same coin. This concept is widely discussed under the term “twin transition.” Nonetheless, entities, whatever their respective size and challenges for being successful, are looking for better understanding DT and its implications as well as appropriate management practices to drive DT not only for their solely competitive benefit but also for the partners, clients, users or even citizens’ benefit. It is of a paramount importance to consider DT as a win-win approach for dramatically increasing entities’ competitiveness while increasing the satisfaction of contributing partners and those using or consuming their offers both in terms of tangible or intangible products. In 2023, the World Economic Forum conducted a survey showing that 87% of respondents foresee DT as disrupting their industries while only half of them declared to be prepared. The DT must take place within the framework of an objective that aims to strengthen competitiveness, sustainability, and resilience, and thus facilitates the implementation of a circular economy. For the European manufacturing industry in particular, this means developing a circular economy value-creation that begins with new business models and concepts for circular product design and extends to fully closed supply chains and remanufacturing concepts for products and components. The development of digital infrastructures, such as those proposed by Gaia-X, as well as their use for concepts like the digital product file and DPP, are indispensable prerequisites. However, this purely digital perspective is far from sufficient. The entire industry is facing the challenge of reorganizing itself at the organizational level, building the necessary capabilities among employees, and ultimately achieving acceptance among people so that behavior can truly change in the context of new business models and new technologies. Therefore, we propose a track on “Digital Transformation for competitiveness and sustainable transformation” with a broad and holistic perspective but focused enough to keep an engineering and technology management perspective.
Review Committee
Chairs
Chair: 
Georges Zissis, IEEE Smart Cities (georges.zissis@laplace.univ-tlse.fr)
Co-Chair: 
Marc Pallot, IEEE TEMS & ICE Community (marc.pallot@9online.fr)
Important Dates
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
Description
Smart City and Living Lab concepts
Scholars presented the concept of Smart Cities in the way the urban development becomes, thanks to digital technologies, more intelligent for dramatically increasing the value creation in better tackling sustainability and competitiveness issues including societal, social, environmental, and economical aspects for whatever city services (Schaffers et al., 2011). Nowadays, the European Commission describes Smart Cities as “a place where traditional networks and services are made more efficient with the use of digital solutions for the benefit of its inhabitants and business. A smart city goes beyond the use of digital technologies for better resource use and less emissions. It means smarter urban transport networks, upgraded water supply and waste disposal facilities and more efficient ways to light and heat buildings. It also means a more interactive and responsive city administration, safer public spaces and meeting the needs of an ageing population.” (EC, 2025). They foresee the wider social and economic impacts, like wellness and competitiveness through “Smart Cities Marketplace” as being “a major market-changing undertaking that aims to bring cities, industries, SMEs, investors, banks, researchers and many other smart city actors together. Their common aims are to improve citizens’ quality of life, increase the competitiveness of European cities and industry as well as to reach European energy and climate targets.”. Schaffers et al. (2011) argued that the Open Innovation (OI) paradigm and Living Lab (LL) concept as well as Digital Transformation (DT) have unleashed the birth of user-driven open innovation ecosystems, often named 4P partnership (Public, Private & People Partnership) and quadruple helix innovation model, for engaging all stakeholders including users allowing to confront technology push and application pull approaches enabling the emergence of breakthrough ideas, concepts and usage scenarios leading to much more adoptable innovative solutions.
Both OI and LL have been widely applied in the context of Smart Cities where “smart” implies DT. Inside the concept of LL is embedded the democratization of innovation towards every citizen in turning users from traditionally observed subjects into active co-creators (Pallot, 2010). This new role for users as co-creators is also a foundation of the Design Thinking method promoted by designers. It is widely admitted that DT impacts our entire society especially through the digital economy and social media enabled by digital technologies implementation inside all organizations within rural and urban regional territories; especially development programs impacting all public institutions and private business sectors. In fact, all entities, either public or private, Large or Small and Medium-sized Enterprises (SMEs) as well as individuals, in their role of users and citizens have the opportunity to innovate their value proposition while dramatically improving their operative mode in applying DT.
Nowadays, well-known technologies have demonstrated their capacity to improve operative factors like, for example, increased anticipation, applicability and resulting value (RoI) through the co-creation, exploration, experimentation and evaluation known as the eXperience Design iterative process for engaging all stakeholders and especially, at the earlier stage, users and citizens (Pallot et al.2010; 2012). These scholars do believe that a better name for this iterative process would be “Value eXperience Design” simply because the design process starts by identifying the value elements to be delivered to customers or citizens, as potential users, and experience factors for being able to evaluate how much these value elements are really delivered in demonstrating RoI, efficiency and reliability through experiments from mockups, prototypes, up to digital twins. Recent research also indicates that Living Lab approaches are increasingly being used to co-create and co-design smart city solutions such as Digital Twins (Willems & Schuurman, 2024) and Data Space use cases (Schuurman, Willems & Robaeyst, 2026).
In addition, a recent study, at the crossroads of Digital Transformation, Social Media, Sustainable Development and the Circular Economy, on the Democratization of Innovation, design, circular engineering and manufacturing through the Do-It-Together (DIT) approach has revealed challenges, induced benefits and potential drawbacks of its implementation (Pallot et al., 2023). Hence, one could envision AI powered Living Labs for helping stakeholders, including citizens, in their duty of co-creating sustainable smart solutions through the implementation of a circular engineering collaborative process. Earlier, a tentative universal framework for systemizing the evaluation of immersive and collaborative performance was described (Dupont et al., 2018).
Furthermore, previous research on the DIT approach has shown that smart cities, hosting innovation labs (fab lab, fab living lab, makerspace, etc.), appear to have the potential to support ecosystemic engineering and generate collaborative ecosystems that are relevant for innovative manufacturing processes considering sustainability factors (Dupont, et al. 2023, Dupont, 2025). The presence of collaborative and hybrid production spaces in cities provides a fertile ground for the emergence of circular activities (Kasmi et al. 2022). The rise of advanced technologies facilitates the development of such hybrid production models, fostering new localized organizational structures based on community engagement, commons, and shared values.
Concepts such as distributed urban production and urban (micro) factories are emerging as viable alternatives; enabling the relocation of manufacturing within cities in a more sustainable and innovative manner (Herrmann et al. 2020). These production systems rely on small-scale, circular and multi-functional manufacturing spaces; leveraging urban resources and local specificities to develop small-batch production models that directly engage consumers as prosumers (Buxbaum-Conradi et al. 2022; Hofer et al. 2024; Dupont et al. 2023).
Thus, the evolution of Smart Cities is intrinsically linked to the reconfiguration of urban manufacturing, where digital transformation enables decentralized, circular, and sustainable production systems. The Horizon Europe LAUDS Factories project exemplifies this shift by fostering Local, Accessible, Urban, Digital Sustainable Factories that integrate advanced manufacturing technologies with participatory innovation models. This project promotes co-creation between citizens, SMEs, creative people, and public stakeholders to design resilient, low-carbon industrial ecosystems. This aligns with the 4P partnership model, where urban manufacturing becomes a driver of local economic development while addressing sustainability challenges. The LAUDS project approach demonstrates how circular engineering and DIT methodologies can democratize industrial innovation, ensuring that Smart Cities are not only digitally enabled but also socially inclusive and environmentally responsible.
Smart Cities increasingly rely on artificial intelligence, urban data platforms, and digital infrastructures to manage complex challenges such as climate adaptation, mobility transitions, and public service delivery. While these technologies enhance cities’ analytical and operational capacities, they also raise fundamental questions about democratic legitimacy, social inclusion, and public trust. Participatory intelligence has emerged as a promising approach to address this tension by integrating structured citizen input into data-driven decision-making processes. By combining deliberative participation with computational methods such as sentiment analysis, cities can better capture collective preferences, values, and concerns, and translate them into actionable knowledge for urban governance (Rezgui et al., 2025).
The Antifragicity project explores how cities can evolve from being merely resilient to becoming antifragile, systems that improve through uncertainty, disruption, and social complexity. The project operationalizes this concept by embedding citizens directly in urban innovation and governance processes through deliberative mechanisms and citizen engagements. Rather than treating participation as an auxiliary activity, Antifragicity positions citizens as co-designers of mobility systems, digital services, and sustainability strategies, as well as continuous contributors to the adaptive capacity of urban institutions. Through iterative experimentation, policy prototyping, and real-world testing, the project demonstrates how citizen input can strengthen institutional learning, policy robustness, and long-term societal acceptance of technological change (Verhasselt et al., 2026). According to Schuurman et al. (2024) “In the current wave of AI innovation, the European Commission has defined Testing and Experimentation Facilities to be established to facilitate AI innovation in the context of new legislation such as the AI act. […] CitCom.ai link[s] these TEFs to longer existing concepts such as testbeds, Living Labs and Regulatory Sandboxes. Our analysis reveals 7 service categories that can be linked to these three innovation concepts. In the 26 analyzed experiments, there was a clear dominance of services linked to the concept of AI testbeds. In second place came three service categories that can be attributed to Living Labs. Remarkably, the service category linked to AI regulatory sandboxes appeared to be the least popular. This reflects the ‘in development’ status of this concept.”
The 2025 updated CitCom.ai European AI Market Report builds upon the insights from the original report from January 2024, offering AI startups across Europe a sharper, more actionable analysis of the current market landscape.
Review Committee
Chairs
Chair: 
Ricardo Jardim-Goncalves, NOVA FCT | UNINOVA
Co-Chair: 
Tal Soffer, Tel Aviv University | Luca Canetta, IEEE TEMS
Important Dates
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
Description

This Special Track focuses on human-centred digital transformation, highlighting the shift from technology-driven to people-driven innovation. As AI, automation, immersive technologies, and connected platforms evolve, organizations increasingly prioritise solutions that enhance human performance, skills, creativity, and collaboration rather than merely optimising processes.

The track combines scientific paper sessions, interactive workshops, and an expert panel discussion to explore emerging architectures, intelligent interfaces, AI-augmented tools, immersive learning environments, and new forms of human–machine collaboration. Contributions span engineering, industry, healthcare, and education, addressing ethical, inclusive, and responsible design. The track aims to bridge research and practice, positioning humans as active drivers of innovation in future-ready digital ecosystems.

Chairs
Chair: 
Carlos Agostinho, UNINOVA
Co-Chair: 
Theodore Dalamagas, ATHENA | Sotiris Koussouris, SUITE5
Important Dates
03 April 2026: Full Paper Submission
08 May 2026: Notification of acceptance
29 May 2026: Camera ready
Description

This Special Session addresses the challenges of transforming AI from experimental prototypes into robust, scalable, and trustworthy systems operating in real-world environments. It focuses on end-to-end AI pipelines, spanning data foundations, model development, deployment, monitoring, and continuous adaptation across the AI lifecycle.

The session brings together recent research and applied experiences in data-centric AI, MLOps, hybrid science- and data-driven models, explainable AI, and human-in-the-loop approaches. Emphasis is placed on techniques that enable AI systems to adapt over time while ensuring transparency, accountability, regulatory alignment, and performance guarantees.

Contributions are invited that bridge methodological advances with industrial practice, showcasing architectures, tools, and lessons learned from complex AI deployments across sectors such as manufacturing, energy, health, and robotics.

Review Committee
  • Ricardo Gonçalves (UNINOVA)
  • Carlos Agostinho (UNINOVA)
  • Theodore Dalamagas (ATHENA)
  • Sotiris Koussouris (SUITE5)
  • George Pallis (Univ. Cyprus)
  • Adrian Asensio (Univ. Polythecnic of Catalonia)
  • Gladys Utrera Iglesias (Univ. Polythecnic of Catalonia)
  • Martin Koerwien (Fraunhofer FOKUS)
  • Stratos Keranidis (DOMX IoT Technologies)
  • Gary McManus (South East Technological University)
  • Ioan Sacala (Univ. P. of Bucharest)
  • Maria Marques (IDEA)
  • João Pedro Mendonça (Univ. of Minho)
Chairs
Chair: 
Dr. Carsten Ellwein, ISW, University of Stuttgart
Co-Chair: 
Dr. Joachim Lentes, Fraunhofer IAO | Nico Jansen, RWTH Aachen
Important Dates
10 April 2026: Full Paper Submission
08 May 2026: Notification of acceptance
29 May 2026: Camera ready
Description

This Special Session explores how modular, ecosystem-based approaches can enable the transition from rigid industrial value chains to dynamic value networks in the context of Software-Defined Manufacturing (SDM). While digitalisation has created significant innovation potential, many industrial initiatives still face challenges related to scalability, complexity, cost, and adoption.

The session addresses technological, organisational, and human-centred perspectives that support ecosystem-driven manufacturing, where interoperable software, hardware, standards, and processes enable continuous, distributed value creation. Contributions are invited that identify structural limitations of current production systems, as well as concept papers, architectures, case studies, and partial solutions that advance modular ecosystems and SDM practices across industrial domains.

Review Committee
  • Bianca Wiesmayr (Business Informatics – Information Engineering, JKU Linz)
  • Dimitri Petrik (BWI, University of Stuttgart)
  • Michel Albonico (MMMI, University of Southern Denmark)
  • Valeria Borodin (IMT, Atlantique Bretagne-Pays de la Loire)
  • Friederike Bruns (DCIS, Carl von Ossietzky University of Oldenburg)
  • Stefan Klikovits (Business Informatics – Information Engineering, JKU Linz)
  • Christian Friedrich (IRP, Karlsruhe University of Applied Sciences)
  • Oliver Kopp (SWK, University of Hamburg)
  • Florian Stamer IPTA, Leuphana University Lüneburg)
  • Kevin Feichtinger (Karlsruhe Institute of Technology)
  • Koren István (ELTE, Eötvös Loránd University)
  • Holger Eichelberger (SSE, University of Hildesheim)
  • Matteo Martinelli (Modena e Reggio Emilia)
  • Alireza Mousavi (College of Engineering, Brunel University London)
  • Sandra Greiner (IMADA, University of Southern Denmark)
  • Kristof Meixner (Vienna University of Technology)
Chairs
Chair: 
Raul Poler, UPV
Co-Chair: 
Miguel Angel Mateo-Casali, UPV
Important Dates
10 April 2026: Full Paper Submission
8 May 2026: Notification of acceptance
29 May 2026: Camera ready
Description

This Special Session addresses the transition towards AI-enabled, service-oriented manufacturing systems, focusing on how manufacturing capabilities can be engineered, deployed, and evaluated as interoperable digital services. While AI adoption in manufacturing is accelerating, significant challenges remain in integrating AI-based services across organisational boundaries while ensuring performance, trust, scalability, and governance.

The session focuses on interoperable architectures, integration of AI components across the edge–shop-floor–cloud continuum, and the validation of AI-enabled manufacturing services in realistic industrial settings. Contributions are invited that present engineering approaches, deployment strategies, industrial case studies, and evaluation frameworks, bridging the gap between research prototypes and deployable, robust industrial solutions for planning, scheduling, quality, maintenance, and resource coordination.

Review Committee
  • Raul Poler (UPV)
  • Miguel Angel Mateo-Casali (UPV)
Chairs
Chair: 
Dr. Nahid Farhady Ghalaty, Microsoft
Co-Chair: 
Jordan Hull, Microsoft | Abhilasha Bhargav-Spantzel, Microsoft | Aditya Aggarwal, Microsoft | Raghu Yeluri, Intel | Sukirna Roy, Microsoft AI
Important Dates
10 April 2026: Full Paper Submission
8 May 2026: Notification of acceptance
29 May 2026: Camera ready
Description

This Special Session focuses on the trustworthy and responsible deployment of autonomous AI agents as a core enabler of digital transformation across enterprises, supply chains, and public services. While agentic AI offers significant potential for competitiveness and efficiency, increased autonomy introduces new challenges related to security, privacy, governance, transparency, and accountability.

The session invites contributions addressing preparedness, runtime supervision, monitoring, and assurance of AI agents operating in complex socio-technical systems. Topics include secure scaling of AI agents, multi-agent trust and communication, privacy-preserving data access, regulatory compliance, and human-centric governance models. Emphasis is placed on real-world deployments, industrial case studies, and validation results that connect technical controls with organizational processes, skills, and responsible innovation practice.

Review Committee
  • Leah Ding - Expert in AI Security (American University)
  • Rosario Cammarota - Expert in Cybersecurity/Threat Intelligence (Intel)
Chairs
Chair: 
Doris Bohnet, Hochschule Konstanz University of Applied Sciences
Co-Chair: 
Corinna Baumgartner, Zurich University of Applied Sciences | Michael Hellwig, Vorarlberg University of Applied Sciences
Important Dates
3 April 2026: Full Paper Submission
30 April 2026: Notification of acceptance
29 May 2026: Camera ready
Description

This Special Session explores the dual role of the Internet of Things (IoT) in advancing environmental sustainability while addressing the sustainability challenges introduced by large-scale IoT deployment. It focuses on how IoT can improve resource efficiency—including water, energy, and raw materials—across industrial and urban ecosystems such as Industry 4.0, smart cities, smart buildings, agriculture, and homes.

The session invites contributions presenting experimental and simulation-based case studies, eco-design and circular approaches for IoT devices and solutions, life cycle assessment (LCA) studies, and analyses of the environmental impact of AI-enabled IoT systems. Emphasis is placed on evidence-based results, comparative studies, and scalable solutions that support sustainable digital transformation.

Review Committee
  • Natalia Burkina (Vorarlberg University of Applied Sciences)
  • Felix Salcher (Vorarlberg University of Applied Sciences)
  • Martin Dobler (Vorarlberg University of Applied Sciences)
  • Steffen Finck (Vorarlberg University of Applied Sciences)
  • Jürg Meierhofer (Zurich University of Applied Sciences)
  • Elodie Chargy (Schneider Electric France)
  • Armin Eberle (Zurich University of Applied Sciences)
  • Mohamed Ramadane (University of Applied Sciences Konstanz)
  • Edward Schreiner (TU Darmstadt)
  • Boris Böck (University of Applied Sciences Konstanz)
  • Omar Mostafa (Karlsruhe Institute of Technology )
Chairs
Chair: 
Rodolfo E. Haber, Spanish National Research Council (CSIC)
Co-Chair: 
Leire Bastida, eServices, TECNALIA, Basque Research and Technology Alliance (BRTA) | Fernando Castano, Spanish National Research Council
Important Dates
10 April 2026: Full Paper Submission
08 May 2026: Notification of acceptance
29 May 2026: Camera ready
Description

This Special Session focuses on next-generation Human–Robot Interaction (HRI) as a key enabler of future industrial and service ecosystems. As collaborative robotics expands across manufacturing, construction, and infrastructure services, humans and robots must interact safely, intuitively, and effectively in dynamic and safety-critical environments.

The session invites contributions addressing AI-driven perception and cognition, multimodal interaction, middleware interoperability, and human-centric approaches for trustworthy and adaptive collaboration. Emphasis is placed on scalable and modular robotic architectures that support safe cooperation and context-aware behaviour. Contributions related to ongoing European initiatives, such as FORTIS, JARVIS, and ARISE, are particularly welcome, bridging advanced HRI research with real-world deployment and industrial impact.

Review Committee
  • Paul Chipendale (Fondazione Bruno Kessler)
  • Micael Couceiro (Ingeniairius)
  • Wael Mohammed (Tampere University)
  • Alberto.villalonga (Spanish National research Council)
  • Yarens J. Cruz (Spanish National research Council)
  • Rui Garcia (Garcia Garcia)
Chairs
Chair: 
Dr. Usman Wajid, Information Catalyst
Co-Chair: 
Alexandros Nizamis, CERTH | Yiannis Verginadis, Athens University of Economics and Business   
Important Dates
17 April 2026: Full Paper Submission
15 May 2026: Notification of acceptance
29 May 2026: Camera ready
Description

This Special Session brings together researchers, innovators, and practitioners to explore dynamic intelligence, connectivity, and automation across the edge–cloud continuum. As distributed systems increasingly span heterogeneous edge and cloud resources, new approaches are required to enable seamless integration, adaptive orchestration, and intelligent resource management.

The session invites high-quality contributions presenting architectures, prototypes, and lessons learned from Horizon Europe projects and related initiatives, as well as independent research on distributed computing. Topics include AI-driven orchestration, security and trustworthiness, energy efficiency, federated learning, swarm intelligence, data spaces, and next-generation hardware and software technologies. The session aims to foster collaboration and shape future directions for cognitive, resilient, and efficient edge–cloud computing infrastructures.

Review Committee
  • Thanasis Kotsiopoulos(CERTH)
  • Ioanna-Aggeliki Kapetanidou (CERTH)
  • Athanasios Liatifis (University of Western Macedonia)
  • Efstathios Karanastasis (National Technical University of Athens)
  • Matilde Julián Seguí (Valencia Polytechnic University)
  • Aleksandra Swoboda (Fujitsu)
  • Gabriel-Mihail Danciu (Siemens)
  • André Gomes (Eclipse Foundation)
  • Nadia Khan (Digital Systems 4.0)
  • Emmanouel (Manos) Varvarigos (National Technical University of Athens)
  • Panagiotis Kokkinos (National Technical University of Athens)
  • Aristotelis Kretsis (National Technical University of Athens)
  • Hui Song (SINTEF)
  • Tamas Kiss (University of Westminster)
  • Amjad Ullah (Edinburgh Napier University)
  • Jozsef Kovacs (HUN-REN SZTAKI)
  • Andras Markus (Institute of Informatics, University of Szeged)
  • Andres Otero (Universidad Politécnica de Madrid)
  • Alessandra Bagnato (Docaposte)
  • Thanasis Moustakas (CERTH)
  • Georgios Spanos (CERTH)
  • Sofia Polymeni (CERTH)
Chairs
Chair: 
Prof. Christos Kalloniatis, University of the Aegean
Co-Chair: 
Prof. Ricardo Jardim Goncalves, New University of Lisbon | José Ferreira, UNINOVA
Important Dates
20 April 2026: Full Paper Submission
10 May 2026: Notification of acceptance
29 May 2026: Camera ready
Description

The Digital Circular Economy workshop explores how advanced digital technologies can accelerate the transition from linear to circular systems across industry, cities, and society. Positioned at the intersection of sustainability, circular economy, and deep tech, the workshop invites researchers, practitioners, innovators, and policymakers to share original contributions on the design, implementation, and impact of digitally enabled circular solutions.

The workshop welcomes work addressing how technologies such as artificial intelligence, IoT, blockchain, robotics, data-driven platforms, and Digital Product Passports can support resource efficiency, product lifecycle transparency, waste reduction, sustainable production, circular business models, and regulatory compliance. Particular emphasis is placed on interdisciplinary approaches that connect technological innovation with education, skills development, governance, and real-world industrial adoption.

Inspired by the vision of Europe’s twin green and digital transition, this workshop aims to create a vibrant forum for exchanging ideas, presenting emerging research, discussing practical applications, and building collaborations across academia, industry, SMEs, and the public sector. We encourage submissions of research papers, case studies, pilot implementations, methodological contributions, and experience reports that demonstrate novel pathways toward a more sustainable, resilient, and digitally driven circular economy.

Review Committee
  • Panagiotis Psomos, University of the Aegean
  • Amir Taherkordi, University of Oslo
  • George Demetriou, Ecode de Ponts Bussiness School
  • Federica Acerbi, Politecnico di Milano
  • Thomas Schröder, Technical University Dortmund
  • Dev Ramanujan, Technical University of Denmark
  • Rebeka Kovačič Lukman, University of Maribor
  • Ioannis Athanasiadis, Wageningen University
  • Christina Alcaraz, University of Malaga
  • Vasco Delgado-Gomes, New University of Lisbon
Chairs
Chair: 
Nuno Amaro, NOVA FCT
Co-Chair: 
Leonor Pereira, EDP
Important Dates
20 April 2026: Full Paper Submission
15 May 2026: Notification of acceptance
29 May 2026: Camera ready
Description
This special session focuses on emerging research, methods, and practical experiences related to energy communities as enablers of a more democratic, flexible, and consumer-centred energy system. It aims to bring together contributions addressing the technological, social, economic, and regulatory dimensions of energy communities, including their role in local energy markets, demand response, peer-to-peer exchange, flexibility provision, and citizen empowerment. Particular attention is given to solutions that help communities create value for their members while also delivering broader system and societal benefits.  Contributions are invited that explore innovative tools, market mechanisms, governance approaches, and policy recommendations supporting the development and scaling-up of energy communities across Europe and beyond. The session seeks to bridge academic advances with lessons learned from real pilot initiatives and EU-funded projects, with special relevance to the objectives of the COMMUNITAS project.  Topics of interest include, but are not limited to: 
  • Energy communities and citizen engagement in the energy transition 
  • Business models, market design, and value creation for energy communities 
  • Demand response, flexibility services, and peer-to-peer energy exchange 
  • Digital platforms, data-driven tools, and decision support for energy communities 
  • Social acceptance, inclusiveness, energy citizenship, and behavioural aspects 
  • Policy, regulation, and governance frameworks for community energy 
By combining perspectives from academia, innovation projects, policymakers, and practitioners, the session will provide a forum to discuss how energy communities can become effective vehicles for a fair, inclusive, and resilient energy transition. 
Review Committee
  • Nuno Amaro (NOVA FCT)
  • Leonor Pereira (EDP)
  • Francisco Ferreira Reis (EDP)
  • Christos Timplalexis (CERTH)
  • Rui Amaral Lopes (NOVA FCT)
  • Sheila Sanchéz (ETRA)
  • Elena Conte (E@W)
  • Chiara Vescovi (RINA)  

Important Dates

ST01 - Artificial Intelligence for Technology Management
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
ST02 - Digital Transformation Management
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
ST03 - Smart Cities
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
ST04 - Digital Transformation for People
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
SS01 - Advancing Adaptive and Trustworthy AI Pipelines
03 April 2026: Full Paper Submission
08 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS02 - Modular Ecosystems for Software-Defined Manufacturing
10 April 2026: Full Paper Submission
08 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS03 - Engineering and Deploying AI-Enabled Manufacturing Services
10 April 2026: Full Paper Submission
8 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS04 - Trustworthy Autonomous AI for Digital Transformation
10 April 2026: Full Paper Submission
8 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS05 - Smart & Sustainable: The Future of Green IoT
3 April 2026: Full Paper Submission
30 April 2026: Notification of acceptance
29 May 2026: Camera ready
SS06 - The Next Generation of Human–Robot Interaction Systems
10 April 2026: Full Paper Submission
08 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS07 - Dynamic Intelligence and Connectivity in the Edge–Cloud Continuum
17 April 2026: Full Paper Submission
15 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS08 - Digital Circular Economy
20 April 2026: Full Paper Submission
10 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS09 - Accelerating the roll-out and expansion of Energy Communities and empower consumers as fully-fledged energy market players
20 April 2026: Full Paper Submission
15 May 2026: Notification of acceptance
29 May 2026: Camera ready
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Call Special Tracks and Sessions 

OVERVIEW

Special Track 01 - Artificial Intelligence for Technology Management
Special Track 02 - Digital Transformation Management
Special Track 03 - Smart Cities
Special Track 04 - Digital Transformation for People:Human-Centric Systems, Skills, and Intelligent Collaboration
Special Session 01 - Advancing Adaptive and Trustworthy AI Pipelines: From Data Foundations to Lifecycle Orchestration and Analytics
Special Session 02 - Modular Ecosystems for Software-Defined Manufacturing: Enabling the Transformation from Value Chains to Value Networks
Special Session 03 - Engineering and Deploying AI-Enabled Manufacturing Services: From Interoperable Architectures to Industrial Adoption and Performance Evaluation
Special Session 04 - Trustworthy Autonomous AI for Digital Transformation: Security, Privacy, Governance, and Transparency of AI Agents
Special Session 05 - Smart & Sustainable: The Future of Green IoT. The Role of IoT in Enhancing System Sustainability and the Need for IoT to Be Sustainable Itself
Special Session 06 - The Next Generation of Human–Robot Interaction Systems: AI-Driven Multimodal Solutions for Safer and Smarter Collaboration
Special Session 07 - Dynamic Intelligence and Connectivity in the Edge–Cloud Continuum: Towards Cognitive Computing Continuums
Special Session 08 - Digital Circular Economy: Digital Deep tech Driven Circular Economy
Special Session 09 -Accelerating the roll-out and expansion of Energy Communities and empower consumers as fully-fledged energy market players

Important Dates

ST01 - Artificial Intelligence for Technology Management
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
ST02 - Digital Transformation Management
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
ST03 - Smart Cities
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
ST04 - Digital Transformation for People
27 Feb 2026 3 April 2026: Full Paper Submission
15 April 2026: Notification of acceptance
29 May 2026: Camera ready
SS01 - Advancing Adaptive and Trustworthy AI Pipelines
03 April 2026: Full Paper Submission
08 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS02 - Modular Ecosystems for Software-Defined Manufacturing
10 April 2026: Full Paper Submission
08 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS03 - Engineering and Deploying AI-Enabled Manufacturing Services
10 April 2026: Full Paper Submission
8 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS04 - Trustworthy Autonomous AI for Digital Transformation
10 April 2026: Full Paper Submission
8 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS05 - Smart & Sustainable: The Future of Green IoT
3 April 2026: Full Paper Submission
30 April 2026: Notification of acceptance
29 May 2026: Camera ready
SS06 - The Next Generation of Human–Robot Interaction Systems
10 April 2026: Full Paper Submission
08 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS07 - Dynamic Intelligence and Connectivity in the Edge–Cloud Continuum
17 April 2026: Full Paper Submission
15 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS08 - Digital Circular Economy
20 April 2026: Full Paper Submission
10 May 2026: Notification of acceptance
29 May 2026: Camera ready
SS09 - Accelerating the roll-out and expansion of Energy Communities and empower consumers as fully-fledged energy market players
20 April 2026: Full Paper Submission
15 May 2026: Notification of acceptance
29 May 2026: Camera ready
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Special Track 01 - Artificial Intelligence for Technology Management

Description
Chair: 
Sudip Chakarborty, IEEE TEMS, sudip.chakarborty@unical.it
Co-Chair: 
Eduardo Ahumada-Tello, IEEE TEMS, eahumada@ieee.org | Robert Bierwolf, ICE Community, robert.bierwolf@xs4all.nl
The Technology Management (TM) concept and “AI for TM” Within Science Direct Social Sciences (SDSS, 2025)Technology Management” is defined by AI generated definition based on [Reference Module in Social Sciences, 2024] “as the strategic alignment of technology with organizational goals, fostering innovation, and navigating the complexities of the technological landscape to achieve sustainable success. It involves embracing recent trends and best practices, such as agile development and data analytics, to drive organizational success in the digital era.” It is well admitted that Technology Management is composed of different activities, such as planning, design, optimization, operation and control of technological products, and related processes as well as services. It includes several disciplines, namely: strategy, forecasting, road mapping, portfolio and transfer that allow any organization to manage whatever technology implementation leading to an increase of competitiveness. The TM concept includes technology strategy, forecasting, scouting, road mapping, and transfer. White & Bruton (2010) define TM as a management process to plan, develop, implement, monitor, and control technological capabilities contributing to fulfill the organization goals. Gajda et al. (2025), argue that “AI-based innovation management has developed into a rapidly expanding and influential research field, moving from marginal attention in the early 2000s to a mainstream domain after 2018. The field integrates technological, managerial, and societal perspectives, with themes ranging from generative AI and decision support to sustainability, open innovation, and organizational change. Research confirms that AI functions both as a practical tool for improving processes and as a transformative force redefining knowledge creation and foresight. Overall, AI-based innovation management has matured into a cornerstone of digital transformation, offering both theoretical advances and practical tools for organizations seeking sustainable competitiveness in the knowledge economy.” According to Corvello (2025), innovation managers “face similar challenges when it comes to appropriating GenAI for product development and R&D processes. A study by Cimino et al. (2024) found that innovation managers in the automotive industry are using GenAI to simulate new vehicle designs and test prototypes in virtual environments. This allows firms to identify potential design flaws before building physical prototypes, reducing costs and speeding up the innovation process. However, as with project managers, the level of appropriation varies significantly depending on the individual’s expertise and the organization’s culture.” Bilgram and Laarmann (2023) argue that generative artificial intelligence (GenAI) allows to democratize the use of AI in innovation management and consequently change both work and innovation approaches. Their experimentation with LLMs in the early phases of innovation and prototyping revealed the following three major insights: (1) there is a plethora of use cases ranging from user journey mapping to idea generation and prototyping where LLMs can support users on how to complete, for example, methodological support for designing an interview guideline and apply knowledge to perform tasks like answering questions for needs along the user journey. Authors foresee a promising role LLMs may play in future knowledge management systems based on LLMs tapping external sources. (2) GenAI, through the use of artificial agents, could become a game changer in early prototyping resulting in faster iterations and reduced costs as well as allowing users getting competencies in new fields and prototype functionalities. Authors foresee a potentially rapid progress in the emergence of specialized AI design tools for high quality design prototyping replacing the manual digital one in early phases. (3) authors experiences show that LLMs imply to reconsider the way innovation teams purposively and effectively interact with AIs and their integration into their workflows. They argue also that involved managers pointed out that “AI-generated information often resembles a draft version created by a skilled human assistant”. They found that this approach is easier and less time-consuming for editing a version than producing initial thoughts. Overall, authors argue that innovation methods, like design thinking, need to be reconsidered in order to seize these above-mentioned GenAI opportunities. Brem et al. (2023) discuss the diverse ways AI is transforming innovation. They present a conceptual framework in which they argue AI plays the following two roles: originator and facilitator of innovation. They also discuss different applications and implications for innovation theory and practice using a reflection on the traditional innovation process and the Front-End of Innovation (FEI) perspective. For this, authors use the perspectives of AI as technology push, AI as market pull, AI to advance steps in the innovation funnel as well as AI as a contributor to New Product Development (NPD). Authors provide (Fig. 1) a final overview of their introduced view of AI as an originator and a facilitator. These perspectives can be linked to key areas/research questions in innovation research. Cooper (2024) proposed an exploratory journey through a mapping exercise crossing the role of AI alongside the innovation funnel stages, starting from the Front-End of Innovation (FEI) to the Back-End of Innovation (BEI) including the postlaunch period. He rightly points out that AI in New Product Development (NPD) was initiated, in fact expert systems, in the late 1970s and early 1980s allowing to automatize complex stage-gates processes mimicking decision-making capabilities of human experts. It happens simultaneously with the Computer-Aided Design & Computer-Aided Manufacturing (CAD/CAM) revolution in the NPD process. It is worth mentioning that apart the technology-based evolution of NPD, new methodological approaches, like System Engineering, Concurrent Engineering, and Circular Engineering have also revolutionized the entire NPD process. Cooper relates that a search for existing AI apps reveals lot of them within the NPD process from FEI idea generation to BEI product launch. He proposes a mapping between AI apps/role and NDP stages (fig. 2) for clarifying their roles, timing, location, and nature in order to better understand this complex AI-NPD landscape According to Cooper and Brem (2024), AI adoption in NPD remains particularly low in the FEI as shown by a study revealing that AI use across five predevelopment activities averaged just 6% while 78% of firms are not using AI for any of these FFE tasks. Cooper (2025) explores the Fuzzy Front-End (FFE) of the NPD process where AI creates new product ideas while comparing all of them according to a set of specified criteria allowing AI to prioritize the best ideas. He provides examples of AI for ideation and screening ideas that reveal positive results through the automation of repetitive tasks quickly leading to valuable insights, hence, more accurate decisions. He also demonstrates, based on provided examples, that AI can also conduct market and competitive analysis while assisting in market research and customer feedback, reducing costs as well as accelerating development timelines with higher NPD success rates. According to Mubarak et al. (2025), strategic leadership, cross-functional collaboration, and a commitment to continuous learning allow to deliver the full potential of AI implementation in the NPD process. Furthermore, authors argue that talent acquisition, ethical and legal concerns, and organizational resistance remain challenges to overcome by proactive management and investment in AI for ensuring a long-term success. Nonetheless, authors mention the following managerial implications: (1) setting-up a necessary NPD governance framework for responsible and ethical use of AI; (2) conform to regulatory requirements regarding data privacy and security like the recent EU AI Act, which is the first legal framework and regulation on AI ensuring that firms develop and use human-centric and trustworthy AI systems; (3) launch specific change management and stakeholder engagement strategies including a necessary cultural shift toward embracing data-driven decision-making for ensuring a successful AI implementation within the NPD process for remaining competitive (Palzer, 2022).
Review Committee:

Special Track 02 - Digital Transformation Management

Description
Chair: 
Luca Canetta, IEEE TEMS (luca.canetta@supsi.ch)
Co-Chair: 
Ricardo Jardim Gonçalves, ICE Community (rg@uninova.pt) | Gerhard Gudergan, ICE Community (Gerhard.Gudergan@fir.rwth-aachen.de)
The Digital Transformation Concept
It is widely admitted that Digital Transformation (DT) impacts our entire society especially through the Digital Economy (DE) and in particular all business sectors. In fact, all entities, either public or private, Large or Small and Medium-sized Enterprises (SMEs) as well as individuals have the opportunity to innovate their value proposition while dramatically improving their operative mode in applying digital technologies. Nowadays, well-known technologies, such as: Mobile, Social-Networks (SN), Big-Data (BD), Artificial Intelligence (AI), Internet of Things (IoT), eXtended Reality (XR), Additive Manufacturing (AM), just to cite a few, have demonstrated their capacity to improve operative factors like, for example, increased effectiveness, efficiency, reliability and replicability of operational processes. Recently, scholars like Gong & Ribiere (2021) argued that existing literature demonstrates evidence of lacking a universal and comprehensive understanding of the DT concept leads to a misunderstanding of the essence of this phenomenon. Consequently, they attempted to formalize a unified definition of DT as follow: “A fundamental change process, enabled by the innovative use of digital technologies accompanied by the strategic leverage of key resources and capabilities, aiming to radically improve an entity* and redefine its value proposition for its stakeholders.” (* An entity could be: an organization, a business network, an industry, or society).

The Twin Transition Concept
In recent years, digital transformation has gained even greater importance than before. It is regarded as a key enabler for fundamentally restructuring supply chains and the associated digital ecosystems; especially since the European Union new Digital Product Passport (DPP) regulation. This transformation aims to increase resilience and facilitate the traceability of life-cycle data towards a transition on circular material and product cycles. In this context, digitalization and the circular economy are increasingly seen as two sides of the same coin. This concept is widely discussed under the term “twin transition.” Nonetheless, entities, whatever their respective size and challenges for being successful, are looking for better understanding DT and its implications as well as appropriate management practices to drive DT not only for their solely competitive benefit but also for the partners, clients, users or even citizens’ benefit. It is of a paramount importance to consider DT as a win-win approach for dramatically increasing entities’ competitiveness while increasing the satisfaction of contributing partners and those using or consuming their offers both in terms of tangible or intangible products. In 2023, the World Economic Forum conducted a survey showing that 87% of respondents foresee DT as disrupting their industries while only half of them declared to be prepared. The DT must take place within the framework of an objective that aims to strengthen competitiveness, sustainability, and resilience, and thus facilitates the implementation of a circular economy. For the European manufacturing industry in particular, this means developing a circular economy value-creation that begins with new business models and concepts for circular product design and extends to fully closed supply chains and remanufacturing concepts for products and components. The development of digital infrastructures, such as those proposed by Gaia-X, as well as their use for concepts like the digital product file and DPP, are indispensable prerequisites. However, this purely digital perspective is far from sufficient. The entire industry is facing the challenge of reorganizing itself at the organizational level, building the necessary capabilities among employees, and ultimately achieving acceptance among people so that behavior can truly change in the context of new business models and new technologies. Therefore, we propose a track on “Digital Transformation for competitiveness and sustainable transformation” with a broad and holistic perspective but focused enough to keep an engineering and technology management perspective.
Review Committee:

Special Track 03 - Smart Cities

Description
Chair: 
Georges Zissis, IEEE Smart Cities (georges.zissis@laplace.univ-tlse.fr)
Co-Chair: 
Marc Pallot, IEEE TEMS & ICE Community (marc.pallot@9online.fr)
Smart City and Living Lab concepts
Scholars presented the concept of Smart Cities in the way the urban development becomes, thanks to digital technologies, more intelligent for dramatically increasing the value creation in better tackling sustainability and competitiveness issues including societal, social, environmental, and economical aspects for whatever city services (Schaffers et al., 2011). Nowadays, the European Commission describes Smart Cities as “a place where traditional networks and services are made more efficient with the use of digital solutions for the benefit of its inhabitants and business. A smart city goes beyond the use of digital technologies for better resource use and less emissions. It means smarter urban transport networks, upgraded water supply and waste disposal facilities and more efficient ways to light and heat buildings. It also means a more interactive and responsive city administration, safer public spaces and meeting the needs of an ageing population.” (EC, 2025). They foresee the wider social and economic impacts, like wellness and competitiveness through “Smart Cities Marketplace” as being “a major market-changing undertaking that aims to bring cities, industries, SMEs, investors, banks, researchers and many other smart city actors together. Their common aims are to improve citizens’ quality of life, increase the competitiveness of European cities and industry as well as to reach European energy and climate targets.”. Schaffers et al. (2011) argued that the Open Innovation (OI) paradigm and Living Lab (LL) concept as well as Digital Transformation (DT) have unleashed the birth of user-driven open innovation ecosystems, often named 4P partnership (Public, Private & People Partnership) and quadruple helix innovation model, for engaging all stakeholders including users allowing to confront technology push and application pull approaches enabling the emergence of breakthrough ideas, concepts and usage scenarios leading to much more adoptable innovative solutions.
Both OI and LL have been widely applied in the context of Smart Cities where “smart” implies DT. Inside the concept of LL is embedded the democratization of innovation towards every citizen in turning users from traditionally observed subjects into active co-creators (Pallot, 2010). This new role for users as co-creators is also a foundation of the Design Thinking method promoted by designers. It is widely admitted that DT impacts our entire society especially through the digital economy and social media enabled by digital technologies implementation inside all organizations within rural and urban regional territories; especially development programs impacting all public institutions and private business sectors. In fact, all entities, either public or private, Large or Small and Medium-sized Enterprises (SMEs) as well as individuals, in their role of users and citizens have the opportunity to innovate their value proposition while dramatically improving their operative mode in applying DT.
Nowadays, well-known technologies have demonstrated their capacity to improve operative factors like, for example, increased anticipation, applicability and resulting value (RoI) through the co-creation, exploration, experimentation and evaluation known as the eXperience Design iterative process for engaging all stakeholders and especially, at the earlier stage, users and citizens (Pallot et al.2010; 2012). These scholars do believe that a better name for this iterative process would be “Value eXperience Design” simply because the design process starts by identifying the value elements to be delivered to customers or citizens, as potential users, and experience factors for being able to evaluate how much these value elements are really delivered in demonstrating RoI, efficiency and reliability through experiments from mockups, prototypes, up to digital twins. Recent research also indicates that Living Lab approaches are increasingly being used to co-create and co-design smart city solutions such as Digital Twins (Willems & Schuurman, 2024) and Data Space use cases (Schuurman, Willems & Robaeyst, 2026).
In addition, a recent study, at the crossroads of Digital Transformation, Social Media, Sustainable Development and the Circular Economy, on the Democratization of Innovation, design, circular engineering and manufacturing through the Do-It-Together (DIT) approach has revealed challenges, induced benefits and potential drawbacks of its implementation (Pallot et al., 2023). Hence, one could envision AI powered Living Labs for helping stakeholders, including citizens, in their duty of co-creating sustainable smart solutions through the implementation of a circular engineering collaborative process. Earlier, a tentative universal framework for systemizing the evaluation of immersive and collaborative performance was described (Dupont et al., 2018).
Furthermore, previous research on the DIT approach has shown that smart cities, hosting innovation labs (fab lab, fab living lab, makerspace, etc.), appear to have the potential to support ecosystemic engineering and generate collaborative ecosystems that are relevant for innovative manufacturing processes considering sustainability factors (Dupont, et al. 2023, Dupont, 2025). The presence of collaborative and hybrid production spaces in cities provides a fertile ground for the emergence of circular activities (Kasmi et al. 2022). The rise of advanced technologies facilitates the development of such hybrid production models, fostering new localized organizational structures based on community engagement, commons, and shared values.
Concepts such as distributed urban production and urban (micro) factories are emerging as viable alternatives; enabling the relocation of manufacturing within cities in a more sustainable and innovative manner (Herrmann et al. 2020). These production systems rely on small-scale, circular and multi-functional manufacturing spaces; leveraging urban resources and local specificities to develop small-batch production models that directly engage consumers as prosumers (Buxbaum-Conradi et al. 2022; Hofer et al. 2024; Dupont et al. 2023).
Thus, the evolution of Smart Cities is intrinsically linked to the reconfiguration of urban manufacturing, where digital transformation enables decentralized, circular, and sustainable production systems. The Horizon Europe LAUDS Factories project exemplifies this shift by fostering Local, Accessible, Urban, Digital Sustainable Factories that integrate advanced manufacturing technologies with participatory innovation models. This project promotes co-creation between citizens, SMEs, creative people, and public stakeholders to design resilient, low-carbon industrial ecosystems. This aligns with the 4P partnership model, where urban manufacturing becomes a driver of local economic development while addressing sustainability challenges. The LAUDS project approach demonstrates how circular engineering and DIT methodologies can democratize industrial innovation, ensuring that Smart Cities are not only digitally enabled but also socially inclusive and environmentally responsible.
Smart Cities increasingly rely on artificial intelligence, urban data platforms, and digital infrastructures to manage complex challenges such as climate adaptation, mobility transitions, and public service delivery. While these technologies enhance cities’ analytical and operational capacities, they also raise fundamental questions about democratic legitimacy, social inclusion, and public trust. Participatory intelligence has emerged as a promising approach to address this tension by integrating structured citizen input into data-driven decision-making processes. By combining deliberative participation with computational methods such as sentiment analysis, cities can better capture collective preferences, values, and concerns, and translate them into actionable knowledge for urban governance (Rezgui et al., 2025).
The Antifragicity project explores how cities can evolve from being merely resilient to becoming antifragile, systems that improve through uncertainty, disruption, and social complexity. The project operationalizes this concept by embedding citizens directly in urban innovation and governance processes through deliberative mechanisms and citizen engagements. Rather than treating participation as an auxiliary activity, Antifragicity positions citizens as co-designers of mobility systems, digital services, and sustainability strategies, as well as continuous contributors to the adaptive capacity of urban institutions. Through iterative experimentation, policy prototyping, and real-world testing, the project demonstrates how citizen input can strengthen institutional learning, policy robustness, and long-term societal acceptance of technological change (Verhasselt et al., 2026). According to Schuurman et al. (2024) “In the current wave of AI innovation, the European Commission has defined Testing and Experimentation Facilities to be established to facilitate AI innovation in the context of new legislation such as the AI act. […] CitCom.ai link[s] these TEFs to longer existing concepts such as testbeds, Living Labs and Regulatory Sandboxes. Our analysis reveals 7 service categories that can be linked to these three innovation concepts. In the 26 analyzed experiments, there was a clear dominance of services linked to the concept of AI testbeds. In second place came three service categories that can be attributed to Living Labs. Remarkably, the service category linked to AI regulatory sandboxes appeared to be the least popular. This reflects the ‘in development’ status of this concept.”
The 2025 updated CitCom.ai European AI Market Report builds upon the insights from the original report from January 2024, offering AI startups across Europe a sharper, more actionable analysis of the current market landscape.
Review Committee:

Special Track 04 - Digital Transformation for People:Human-Centric Systems, Skills, and Intelligent Collaboration

Description
Chair: 
Ricardo Jardim-Goncalves, NOVA FCT | UNINOVA
Co-Chair: 
Tal Soffer, Tel Aviv University | Luca Canetta, IEEE TEMS

This Special Track focuses on human-centred digital transformation, highlighting the shift from technology-driven to people-driven innovation. As AI, automation, immersive technologies, and connected platforms evolve, organizations increasingly prioritise solutions that enhance human performance, skills, creativity, and collaboration rather than merely optimising processes.

The track combines scientific paper sessions, interactive workshops, and an expert panel discussion to explore emerging architectures, intelligent interfaces, AI-augmented tools, immersive learning environments, and new forms of human–machine collaboration. Contributions span engineering, industry, healthcare, and education, addressing ethical, inclusive, and responsible design. The track aims to bridge research and practice, positioning humans as active drivers of innovation in future-ready digital ecosystems.

Review Committee:

Special Session 01 - Advancing Adaptive and Trustworthy AI Pipelines: From Data Foundations to Lifecycle Orchestration and Analytics

Description
Chair: 
Carlos Agostinho, UNINOVA
Co-Chair: 
Theodore Dalamagas, ATHENA | Sotiris Koussouris, SUITE5

This Special Session addresses the challenges of transforming AI from experimental prototypes into robust, scalable, and trustworthy systems operating in real-world environments. It focuses on end-to-end AI pipelines, spanning data foundations, model development, deployment, monitoring, and continuous adaptation across the AI lifecycle.

The session brings together recent research and applied experiences in data-centric AI, MLOps, hybrid science- and data-driven models, explainable AI, and human-in-the-loop approaches. Emphasis is placed on techniques that enable AI systems to adapt over time while ensuring transparency, accountability, regulatory alignment, and performance guarantees.

Contributions are invited that bridge methodological advances with industrial practice, showcasing architectures, tools, and lessons learned from complex AI deployments across sectors such as manufacturing, energy, health, and robotics.

Review Committee:
  • Ricardo Gonçalves (UNINOVA)
  • Carlos Agostinho (UNINOVA)
  • Theodore Dalamagas (ATHENA)
  • Sotiris Koussouris (SUITE5)
  • George Pallis (Univ. Cyprus)
  • Adrian Asensio (Univ. Polythecnic of Catalonia)
  • Gladys Utrera Iglesias (Univ. Polythecnic of Catalonia)
  • Martin Koerwien (Fraunhofer FOKUS)
  • Stratos Keranidis (DOMX IoT Technologies)
  • Gary McManus (South East Technological University)
  • Ioan Sacala (Univ. P. of Bucharest)
  • Maria Marques (IDEA)
  • João Pedro Mendonça (Univ. of Minho)

Special Session 02 - Modular Ecosystems for Software-Defined Manufacturing: Enabling the Transformation from Value Chains to Value Networks

Description
Chair: 
Dr. Carsten Ellwein, ISW, University of Stuttgart
Co-Chair: 
Dr. Joachim Lentes, Fraunhofer IAO | Nico Jansen, RWTH Aachen

This Special Session explores how modular, ecosystem-based approaches can enable the transition from rigid industrial value chains to dynamic value networks in the context of Software-Defined Manufacturing (SDM). While digitalisation has created significant innovation potential, many industrial initiatives still face challenges related to scalability, complexity, cost, and adoption.

The session addresses technological, organisational, and human-centred perspectives that support ecosystem-driven manufacturing, where interoperable software, hardware, standards, and processes enable continuous, distributed value creation. Contributions are invited that identify structural limitations of current production systems, as well as concept papers, architectures, case studies, and partial solutions that advance modular ecosystems and SDM practices across industrial domains.

Review Committee:
  • Bianca Wiesmayr (Business Informatics – Information Engineering, JKU Linz)
  • Dimitri Petrik (BWI, University of Stuttgart)
  • Michel Albonico (MMMI, University of Southern Denmark)
  • Valeria Borodin (IMT, Atlantique Bretagne-Pays de la Loire)
  • Friederike Bruns (DCIS, Carl von Ossietzky University of Oldenburg)
  • Stefan Klikovits (Business Informatics – Information Engineering, JKU Linz)
  • Christian Friedrich (IRP, Karlsruhe University of Applied Sciences)
  • Oliver Kopp (SWK, University of Hamburg)
  • Florian Stamer IPTA, Leuphana University Lüneburg)
  • Kevin Feichtinger (Karlsruhe Institute of Technology)
  • Koren István (ELTE, Eötvös Loránd University)
  • Holger Eichelberger (SSE, University of Hildesheim)
  • Matteo Martinelli (Modena e Reggio Emilia)
  • Alireza Mousavi (College of Engineering, Brunel University London)
  • Sandra Greiner (IMADA, University of Southern Denmark)
  • Kristof Meixner (Vienna University of Technology)

Special Session 03 - Engineering and Deploying AI-Enabled Manufacturing Services: From Interoperable Architectures to Industrial Adoption and Performance Evaluation

Description
Chair: 
Raul Poler, UPV
Co-Chair: 
Miguel Angel Mateo-Casali, UPV

This Special Session addresses the transition towards AI-enabled, service-oriented manufacturing systems, focusing on how manufacturing capabilities can be engineered, deployed, and evaluated as interoperable digital services. While AI adoption in manufacturing is accelerating, significant challenges remain in integrating AI-based services across organisational boundaries while ensuring performance, trust, scalability, and governance.

The session focuses on interoperable architectures, integration of AI components across the edge–shop-floor–cloud continuum, and the validation of AI-enabled manufacturing services in realistic industrial settings. Contributions are invited that present engineering approaches, deployment strategies, industrial case studies, and evaluation frameworks, bridging the gap between research prototypes and deployable, robust industrial solutions for planning, scheduling, quality, maintenance, and resource coordination.

Review Committee:
  • Raul Poler (UPV)
  • Miguel Angel Mateo-Casali (UPV)

Special Session 04 - Trustworthy Autonomous AI for Digital Transformation: Security, Privacy, Governance, and Transparency of AI Agents

Description
Chair: 
Dr. Nahid Farhady Ghalaty, Microsoft
Co-Chair: 
Jordan Hull, Microsoft | Abhilasha Bhargav-Spantzel, Microsoft | Aditya Aggarwal, Microsoft | Raghu Yeluri, Intel | Sukirna Roy, Microsoft AI

This Special Session focuses on the trustworthy and responsible deployment of autonomous AI agents as a core enabler of digital transformation across enterprises, supply chains, and public services. While agentic AI offers significant potential for competitiveness and efficiency, increased autonomy introduces new challenges related to security, privacy, governance, transparency, and accountability.

The session invites contributions addressing preparedness, runtime supervision, monitoring, and assurance of AI agents operating in complex socio-technical systems. Topics include secure scaling of AI agents, multi-agent trust and communication, privacy-preserving data access, regulatory compliance, and human-centric governance models. Emphasis is placed on real-world deployments, industrial case studies, and validation results that connect technical controls with organizational processes, skills, and responsible innovation practice.

Review Committee:
  • Leah Ding - Expert in AI Security (American University)
  • Rosario Cammarota - Expert in Cybersecurity/Threat Intelligence (Intel)

Special Session 05 - Smart & Sustainable: The Future of Green IoT. The Role of IoT in Enhancing System Sustainability and the Need for IoT to Be Sustainable Itself

Description
Chair: 
Doris Bohnet, Hochschule Konstanz University of Applied Sciences
Co-Chair: 
Corinna Baumgartner, Zurich University of Applied Sciences | Michael Hellwig, Vorarlberg University of Applied Sciences

This Special Session explores the dual role of the Internet of Things (IoT) in advancing environmental sustainability while addressing the sustainability challenges introduced by large-scale IoT deployment. It focuses on how IoT can improve resource efficiency—including water, energy, and raw materials—across industrial and urban ecosystems such as Industry 4.0, smart cities, smart buildings, agriculture, and homes.

The session invites contributions presenting experimental and simulation-based case studies, eco-design and circular approaches for IoT devices and solutions, life cycle assessment (LCA) studies, and analyses of the environmental impact of AI-enabled IoT systems. Emphasis is placed on evidence-based results, comparative studies, and scalable solutions that support sustainable digital transformation.

Review Committee:
  • Natalia Burkina (Vorarlberg University of Applied Sciences)
  • Felix Salcher (Vorarlberg University of Applied Sciences)
  • Martin Dobler (Vorarlberg University of Applied Sciences)
  • Steffen Finck (Vorarlberg University of Applied Sciences)
  • Jürg Meierhofer (Zurich University of Applied Sciences)
  • Elodie Chargy (Schneider Electric France)
  • Armin Eberle (Zurich University of Applied Sciences)
  • Mohamed Ramadane (University of Applied Sciences Konstanz)
  • Edward Schreiner (TU Darmstadt)
  • Boris Böck (University of Applied Sciences Konstanz)
  • Omar Mostafa (Karlsruhe Institute of Technology )

Special Session 06 - The Next Generation of Human–Robot Interaction Systems: AI-Driven Multimodal Solutions for Safer and Smarter Collaboration

Description
Chair: 
Rodolfo E. Haber, Spanish National Research Council (CSIC)
Co-Chair: 
Leire Bastida, eServices, TECNALIA, Basque Research and Technology Alliance (BRTA) | Fernando Castano, Spanish National Research Council

This Special Session focuses on next-generation Human–Robot Interaction (HRI) as a key enabler of future industrial and service ecosystems. As collaborative robotics expands across manufacturing, construction, and infrastructure services, humans and robots must interact safely, intuitively, and effectively in dynamic and safety-critical environments.

The session invites contributions addressing AI-driven perception and cognition, multimodal interaction, middleware interoperability, and human-centric approaches for trustworthy and adaptive collaboration. Emphasis is placed on scalable and modular robotic architectures that support safe cooperation and context-aware behaviour. Contributions related to ongoing European initiatives, such as FORTIS, JARVIS, and ARISE, are particularly welcome, bridging advanced HRI research with real-world deployment and industrial impact.

Review Committee:
  • Paul Chipendale (Fondazione Bruno Kessler)
  • Micael Couceiro (Ingeniairius)
  • Wael Mohammed (Tampere University)
  • Alberto.villalonga (Spanish National research Council)
  • Yarens J. Cruz (Spanish National research Council)
  • Rui Garcia (Garcia Garcia)

Special Session 07 - Dynamic Intelligence and Connectivity in the Edge–Cloud Continuum: Towards Cognitive Computing Continuums

Description
Chair: 
Dr. Usman Wajid, Information Catalyst
Co-Chair: 
Alexandros Nizamis, CERTH | Yiannis Verginadis, Athens University of Economics and Business   

This Special Session brings together researchers, innovators, and practitioners to explore dynamic intelligence, connectivity, and automation across the edge–cloud continuum. As distributed systems increasingly span heterogeneous edge and cloud resources, new approaches are required to enable seamless integration, adaptive orchestration, and intelligent resource management.

The session invites high-quality contributions presenting architectures, prototypes, and lessons learned from Horizon Europe projects and related initiatives, as well as independent research on distributed computing. Topics include AI-driven orchestration, security and trustworthiness, energy efficiency, federated learning, swarm intelligence, data spaces, and next-generation hardware and software technologies. The session aims to foster collaboration and shape future directions for cognitive, resilient, and efficient edge–cloud computing infrastructures.

Review Committee:
  • Thanasis Kotsiopoulos(CERTH)
  • Ioanna-Aggeliki Kapetanidou (CERTH)
  • Athanasios Liatifis (University of Western Macedonia)
  • Efstathios Karanastasis (National Technical University of Athens)
  • Matilde Julián Seguí (Valencia Polytechnic University)
  • Aleksandra Swoboda (Fujitsu)
  • Gabriel-Mihail Danciu (Siemens)
  • André Gomes (Eclipse Foundation)
  • Nadia Khan (Digital Systems 4.0)
  • Emmanouel (Manos) Varvarigos (National Technical University of Athens)
  • Panagiotis Kokkinos (National Technical University of Athens)
  • Aristotelis Kretsis (National Technical University of Athens)
  • Hui Song (SINTEF)
  • Tamas Kiss (University of Westminster)
  • Amjad Ullah (Edinburgh Napier University)
  • Jozsef Kovacs (HUN-REN SZTAKI)
  • Andras Markus (Institute of Informatics, University of Szeged)
  • Andres Otero (Universidad Politécnica de Madrid)
  • Alessandra Bagnato (Docaposte)
  • Thanasis Moustakas (CERTH)
  • Georgios Spanos (CERTH)
  • Sofia Polymeni (CERTH)

Special Session 08 - Digital Circular Economy: Digital Deep tech Driven Circular Economy

Description
Chair: 
Prof. Christos Kalloniatis, University of the Aegean
Co-Chair: 
Prof. Ricardo Jardim Goncalves, New University of Lisbon | José Ferreira, UNINOVA

The Digital Circular Economy workshop explores how advanced digital technologies can accelerate the transition from linear to circular systems across industry, cities, and society. Positioned at the intersection of sustainability, circular economy, and deep tech, the workshop invites researchers, practitioners, innovators, and policymakers to share original contributions on the design, implementation, and impact of digitally enabled circular solutions.

The workshop welcomes work addressing how technologies such as artificial intelligence, IoT, blockchain, robotics, data-driven platforms, and Digital Product Passports can support resource efficiency, product lifecycle transparency, waste reduction, sustainable production, circular business models, and regulatory compliance. Particular emphasis is placed on interdisciplinary approaches that connect technological innovation with education, skills development, governance, and real-world industrial adoption.

Inspired by the vision of Europe’s twin green and digital transition, this workshop aims to create a vibrant forum for exchanging ideas, presenting emerging research, discussing practical applications, and building collaborations across academia, industry, SMEs, and the public sector. We encourage submissions of research papers, case studies, pilot implementations, methodological contributions, and experience reports that demonstrate novel pathways toward a more sustainable, resilient, and digitally driven circular economy.

Review Committee:
  • Panagiotis Psomos, University of the Aegean
  • Amir Taherkordi, University of Oslo
  • George Demetriou, Ecode de Ponts Bussiness School
  • Federica Acerbi, Politecnico di Milano
  • Thomas Schröder, Technical University Dortmund
  • Dev Ramanujan, Technical University of Denmark
  • Rebeka Kovačič Lukman, University of Maribor
  • Ioannis Athanasiadis, Wageningen University
  • Christina Alcaraz, University of Malaga
  • Vasco Delgado-Gomes, New University of Lisbon

Special Session 09 -Accelerating the roll-out and expansion of Energy Communities and empower consumers as fully-fledged energy market players

Description
Chair: 
Nuno Amaro, NOVA FCT
Co-Chair: 
Leonor Pereira, EDP
This special session focuses on emerging research, methods, and practical experiences related to energy communities as enablers of a more democratic, flexible, and consumer-centred energy system. It aims to bring together contributions addressing the technological, social, economic, and regulatory dimensions of energy communities, including their role in local energy markets, demand response, peer-to-peer exchange, flexibility provision, and citizen empowerment. Particular attention is given to solutions that help communities create value for their members while also delivering broader system and societal benefits.  Contributions are invited that explore innovative tools, market mechanisms, governance approaches, and policy recommendations supporting the development and scaling-up of energy communities across Europe and beyond. The session seeks to bridge academic advances with lessons learned from real pilot initiatives and EU-funded projects, with special relevance to the objectives of the COMMUNITAS project.  Topics of interest include, but are not limited to: 
  • Energy communities and citizen engagement in the energy transition 
  • Business models, market design, and value creation for energy communities 
  • Demand response, flexibility services, and peer-to-peer energy exchange 
  • Digital platforms, data-driven tools, and decision support for energy communities 
  • Social acceptance, inclusiveness, energy citizenship, and behavioural aspects 
  • Policy, regulation, and governance frameworks for community energy 
By combining perspectives from academia, innovation projects, policymakers, and practitioners, the session will provide a forum to discuss how energy communities can become effective vehicles for a fair, inclusive, and resilient energy transition. 
Review Committee:
  • Nuno Amaro (NOVA FCT)
  • Leonor Pereira (EDP)
  • Francisco Ferreira Reis (EDP)
  • Christos Timplalexis (CERTH)
  • Rui Amaral Lopes (NOVA FCT)
  • Sheila Sanchéz (ETRA)
  • Elena Conte (E@W)
  • Chiara Vescovi (RINA)  

Call for Special Sessions Proposals

Special sessions in ICE have demonstrated to be crucial means for deepening knowledge, staying updated on the latest trends, fostering collaborations, and broadening perspectives within a specific field or topic. They contribute significantly to the advancement and evolution of research and innovation.

The ICE 2026 Organising Committee invites proposals for conference special sessions focused on specific topics related to the conference theme.

Conference special sessions should explain the means for soliciting and selecting contributions, proposing an independent review committee.

For a position of larger visibility in the Conference and respective Committee, please submit your proposal to organize and to be chair for a "track" of sessions under the scope of one of the major ICE/IEEE ITMC 2026 conference topcis.

Please fill out the Special Session template and send your proposal to info@ice-conference.org with the subject "Special Session Proposal".

Important Dates

Special Session

30 Jan 2026: Special Sessions proposals
27 Feb 2026: Special Sessions Acceptance Notification
29 May 2026: Special Sessions Camera-ready copies
22-24 June 2026: ICE Conference Special Sessions


Special Sessions

OVERVIEW

SS01 - Special Session: Smart grading, handling, and packaging solutions for soft and deformable products in agile and reconfigurable lines

SS02 - Special Session: AI-Driven Industrial Equipment Product Life Cycle Boosting Agility, Sustainability and Resilience

SS03 - Special Session: Digital Modelling and Simulation for Design, Processing and Manufacturing of Advanced Materials

SS04 - Special Session: Autonomous and Self-organized Artificial Intelligent Orchestrator for a Greener Industry 4.0

SS05 - Special Session: Non-destructive inspection technologies for sustainable manufacturing: Zero Waste and Zero Defects approach

SS06 - Special Session: Advancing Human Robot Collaboration in Industry 5.0

SS07 - Special Session: Urban digital and ecological transformation – an IT-engineering perspective

SS08 - Special Session: AI, Data, and Robotics for a Sustainable Food Supply Chain

SS09 - Special Session: Business Applications of Artificial Intelligence, Data Analytics, and Optimization

SS10 - Special Session: AI for Smart Engineering

SS11 - Special Session: Advanced technical solutions for building management and energy monitoring

SS12 - Special Session: Advancing the European Green Deal: Integrating EDIHs and Innovation Ecosystems for Sustainable Transformation

SS13 - Special Session: Manufacturing-As-A-Service (MaaS) and Smart Manufacturing Networks: A New Era of Supply Chain Resilience

SS14 - Special Session: Cognitive Computing Continuum

Important Dates

SS01: Smart grading, handling, and packaging solutions for soft and deformable products in agile and reconfigurable lines

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS02: AI-Driven Industrial Equipment Product Life Cycle Boosting Agility, Sustainability and Resilience

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS03: Digital Modelling and Simulation for Design, Processing and Manufacturing of Advanced Materials

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS04: Autonomous and Self-organized Artificial Intelligent Orchestrator for a Greener Industry 4.0

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS05: Non-destructive inspection technologies for sustainable manufacturing: Zero Waste and Zero Defects approach

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS06: Advancing Human Robot Collaboration in Industry 5.0

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS07: Urban digital and ecological transformation – an IT-engineering perspective

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS08: AI, Data, and Robotics for a Sustainable Food Supply Chain

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS09: Business Applications of Artificial Intelligence, Data Analytics, and Optimization

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS10: AI for Smart Engineering

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

SS11: Advanced technical solutions for building management and energy monitoring

16 Mar 2025: Full Paper Submission
31 Mar 2025: Paper Notification of Acceptance

ST001 - Special Track: Data-Driven and Impact-Oriented Entrepreneurship Research

Description
Chair: Dr. Kevin Reuther - University, Fraunhofer IMW
Co-Chair: Prof. Yngve Dahle - University of South-Eastern Norway, Fraunhofer IMW

Entrepreneurship constitutes an important factor for economic growth, societal progression as well as individual self-realization. It is broadly defined as an activity that involves the discovery, evaluation and exploitation of opportunities to introduce new goods and services, ways of organizing, markets, processes, and raw materials. In recent years, there has been an increasing call for data-driven and evidence-based research to help understanding how entrepreneurial activities can best be supported, what components and surrounding factors make successful entrepreneurial ecosystems and what established companies can learn from entrepreneurial activities. Moreover, the exploration of opportunities from emerging technologies (e.g., artificial intelligence, nanotechnology, quantum computing, etc.) has gained traction, investigating how deep tech start-ups contribute to solving complex social and environmental challenges such as climate change, human health, advances systems and infrastructure. This special track comprises four sessions focusing on different areas in the entrepreneurship research field. Each session invites high-quality papers contributing to data-driven and impact-oriented research in the entrepreneurship field using new methods, novel datasets or novel perspectives on established datasets and focusing on the impact generated by or for the entrepreneurial activities to be investigated.

  • The Role of Robotics in Industry 5.0
  • Creative Robotics in Industry 5.0
  • Human-Centric Approaches to Robotics and Automation
  • Sustainable Manufacturing Practices
  • Technological Innovations for Industry 5.0
  • Technological Synergies for a Sustainable Future
Review Committee:
  • André Rocha - UNINOVA
  • José Barata - UNINOVA
  • Sanaz Nikghadam - UNINOVA
  • Luís Ribeiro - Linköping University
  • Nelson Rodrigues - DTx
  • Pedro Ferreira - Loughborough University
Event Location

Alfândega Porto Congress Center
Porto, Portugal

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