Working Groups

Smart Society refers to urban societies that are growing rapidly and becoming increasingly complex and reliant on large infrastructures. For example, the need for efficient and sustainable transportation increases steadily, and it is becoming evident that radically new solutions for mobility are required in order to fulfil the increasing demands while at the same time improving sustainability.

Chair: Mattias Höjer

Digitalized industry is focusing on disruptive innovations in product and service design, manufacturing and process automation. New paradigms provide the potential for drastic enhancement of product design and manufacturing through automation, connectivity, integration, modelling and simulation, and data handling/exploitation. This provides strong potential for manufacturing flexibility, product customisation, and using all of these new capabilities to drive sustainability and a transition to a circular economy.

Chair: Martin Törngren

Rich and healthy life concerns how digital interactions and technologies may bring richness, meaning and health to our everyday lives. The theme spans topics from health and wellbeing – including physical and mental wellbeing – to sports, enjoyment, games, access to culture, nature, food, and in general leading a good life.

Chair: Elena Gutierrez Farewik

Educational transformation handles modern digital technologies, AI and access to data to provide new opportunities to develop education and ways of learning. Therefore, research on technology-enhanced learning and evidence-based development of curricula, education tools and pedagogics are essential components within this context.

Chair: Joakim Lilliesköld

Trust emphasises the development of mechanisms that create and ensure trust in societal transformation in general as well as in specific engineered systems. Essential challenges are found within the intersection of privacy and information security to enable trust between users and systems.

Chair: Henrik Sandberg

Cooperate recognises that systems are to an ever-increasing degree distributed and interconnected; creating new opportunities, but also increasing design and implementation complexity. Although decisions and operations may be distributed, the system components need to be cooperatively designed to ensure flexibility, efficiency and resilience. Furthermore, technology should support the collaboration between humans, and between humans and intelligent systems.

Chair: György Dán

Learn involves how to extract information from data that makes systems smart and adaptive or even autonomous. Since the generation and storage of data will often be distributed, there is a strong need for efficient distributed data analytics. A fundamental understanding of how machine learning algorithms extract information from data is still missing, and the impact of the data on the learning process and the resulting bias is hardly understood. This gives rise to questions concerning legal safeguards and the rule of law.

Chair: Ozan Öktem