Research centre established by:

KTH, Stockholm University and RISE
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Working Groups

The Working Groups address the societal challenges and research themes that the Digital Futures Strategic Research Programme focuses on; Smart Society, Digitalized Industry, Rich and Healthy Life, Educational Transformation, Trust, Cooperate and Learn. The Working Groups are chaired by members of the Strategic Research Committee.

If you are interested in joining any of the working groups, please feel free to contact the respective chair.

Red outline of three stylised buildings of varying heights, including one tall structure with windows, on a light background.Smart Society

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

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Red gear icon with circuit-like lines extending from the right side, symbolising the integration of technology and engineering or digital transformation.Digitalized Industry

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

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Red outline of a hand holding icons of a heart, a plus sign, and a star, symbolising care, health, and excellence.Rich and Healthy Life

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: Arvind Kumar

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Red outline of a lightbulb with a brain inside it, symbolising creativity or an idea, with small lines around the bulb representing light.Educational Transformation

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: Olga Viberg

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A simple red shield outline with a red tick in the centre, symbolising security or protection.Trust

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

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Red outline drawing of two hands shaking, symbolising agreement or partnership, on a light background.Cooperate

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

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Red outline of a brain on the left, with circuit-like lines extending to the right, symbolising the connection between artificial intelligence and technology.Learn

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: Kathlén Kohn

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