COLDµWAVE aims to improve the research skills of Epameinondas Xanthakis by developing an innovative environmentally sustainable process for blanching and freezing vegetables with improved textural and nutritional quality at SP -Technical Research Institute of Sweden. The study which will be carried out will involve the use of microwave electromagnetic irradiation (MW) for blanching and freezing of vegetables. COLDµWAVE will develop tailored equipment for MW blanching of vegetables that has very high energy efficiency and no water consumption. Furthermore, this project will develop innovative pathways in freezing to improve the quality of frozen vegetables by exploring, in a new context, previous results acquired by the fellow. The developed process will lead to improved quality characteristics compared to the conventional freezing. During this extensive study the fellow will gain valuable multidisciplinary experience and new theoretical and practical skills in the areas of heat transfer modelling, energy accounting methods, food nutrition and quality measurements as well as life cycle assessment methods. The integrated proposed study will give the fellow the opportunity to develop further knowledge on development of innovative processes having industrial importance and finally become a real specialist in the microwave assisted food blanching and freezing. The candidate will also learn to conduct research, to manage projects, communicate results effectively, commercialise research, as well as an in-depth education in development of innovative processes which will contribute for an open mind to innovation and more successfully realisation of research ideas into commercial reality.

Artificial Neural Networks (ANNs) form the main approach in Artificial Intelligence (AI). They have two major drawbacks, however: (1) ANNs require significant computational resources; (2) they lack transparency. These challenges restrict the widespread application of AI in daily life. The required resources prevent the use of ANNs on resource-constrained devices and the lack of transparency limits their adoption in many areas where transparency is critical. This action will address these challenges via development of Vector Symbolic Architectures (VSAs): a transparent, bio-inspired framework for AI. With respect to the 1st challenge, VSAs have the potential to become a computational paradigm for emerging low-power computing hardware with huge potential for implementing AI algorithms. With respect to the 2nd challenge, VSAs are a promising framework for opening the black box of ANNs due to their predictable statistical properties. It is expected that VSAs will allow analytical characterization of a class of Recurrent ANNs. The overall research aim of this action is to improve the understanding of computing principles in high-dimensional spaces with VSAs, and to advance the theory and design principles of simple AI algorithms implementable on emerging low-power computing hardware. The research aim comprises five research objectives. These are relevant to H2020 Work Programme since this action has much potential with respect to the “market creating innovation” and “digitising and transforming industry” aspects of the Programme. The mechanisms for achieving the objectives include both theoretical development and applied investigations. The methodological approach combines the current skills of the applicant with those acquired during this action. The applicant will develop VSAs skills to qualitatively higher level while working under the supervision of eminent researchers. This will enhance applicant’s professional maturity and prepare him for an independent career.

The MIMER AI Innovation Factory proposal, led by Linköping University (LiU) and RISE, will establish a groundbreaking AI Factory in Sweden to accelerate the adoption of AI across academia, industry, and public sectors in alignment with Swedish and European strategic priorities. The AI Factory will serve as a collaborative hub, providing seamless access to AI-optimized supercomputing resources and promoting innovation in sectors such as life sciences, materials science, autonomous systems, and the gaming industry. We will offer support services to help users maximize the benefits of AI in HPC environments. Through structured onboarding, the Factory guides new users in framing AI problems, organizing data, and selecting tools for model training. A competency-based knowledge system also assists users, particularly those new to AI, in identifying skill levels and accessing relevant training. RISE will lead the efforts in engaging SME users, providing tailored support and expertise to help them integrate AI into their operations, while LiU will focus on academic and research-based users. The training and workforce development are designed to address the increasing demand for AI skills, offering hands-on training, workshops, and events to support AI literacy and build a skilled workforce across Europe. By aligning with EuroHPC, we will engage in active partnerships with other European AI initiatives, supporting joint projects and data-sharing frameworks that ensure compliance with EU data privacy and AI regulations. The factory will democratize access to advanced AI infrastructure and expertise. It will empower a broad range of users, including academia, SMEs, and industry leaders, to develop cutting-edge AI applications. By promoting innovation, enhancing productivity, and supporting sustainable AI practices, the Factory will position Sweden as a strong hub in the European AI ecosystem, driving scientific excellence, technological advancement, and economic growth.

Intimate Touch will re-conceptualise how technologies use touch to interact with us. Bringing intimacy as a lens on touch inspires us to think about the felt experience of touch, the diversity of places on the body where we will be touched by technology, and the sense that touch can be transformative of our view of ourselves. This project will develop the theory, methods and technologies of Intimate Touch. It will bring together research in Human-Computer Interaction on intimate technologies with new interaction techniques, alongside psychological theories on intimacy and neuroscience perspectives on touch. Technologies that touch us will constitute a new paradigm of interactive devices, most strongly exemplified by care robots. Designing technologies for Intimate Touch will be foundational in creating dignified and acceptable interactions between humans and technologies. The first objective is to develop a model of ‘intimate technology’. No researcher has done this before. This model will be developed through a large-scale interview study alongside in-situ, long-term studies of our own demonstrators of Intimate Touch. By identifying which interactions lead to intimacy, this project will have empirically identified a new class of technology, ‘intimate technology’. Autonomous systems will touch many areas of our bodies. Yet, there has been no serious study of touch experiences other than on the hands and shoulders. My second objective will counter this by innovating on a design approach that centres the felt experience of touch from technology, and by creating a dataset that describes people’s experience of touch from technology across the body. My final objective is to develop two demonstrators of Intimate Touch. This risky challenge will evidence how touch with technology transforms us. Practically this will provide a roadmap to good touch from technology. Empirically this will lay the groundwork for a re-conceptualization of our relationship with technology