AI-based self control for each distributed energy source
Researchers at KTH have developed an open-source artificial intelligence (AI) solution to counter the challenges posed by integrating renewable energy and electric vehicles (EVs) in power grids. The increasing reliance on variable sources like solar and wind, combined with the […]
Read moreSwedish delegation and Crown Princess Couple explores AI collaboration in Silicon Valley
Karl Henrik Johansson, Director of Digital Futures, was part of a delegation from the Royal Swedish Academy of Engineering Sciences (IVA) that visited Silicon Valley from February 19 to 22. The delegation included DD.KK.HH., the Crown Princess, and Prince Daniel, […]
Read moreInnovative technique revolutionizes bioelectronics and critical sensors prototyping
A research team at KTH Royal Institute of Technology and Stockholm University has made a bioelectronics and sensor technology breakthrough. The team unveiled a fast-prototyping technique utilizing a standard Nanoscribe 3D microprinter, revolutionizing the fabrication of electrochemical transistors. Without needing […]
Read moreDigital Futures Drone Arena – watch the spectacular Drone Challenges video
In a groundbreaking display of innovation and creativity, the Digital Futures-funded project Drone Arena recently released a video of the Drone Challenges. The events, held in June 2022 and May 2023 at KTH’s Reactor Hall in Stockholm, Sweden, showcased the […]
Read moreOpen call: Up to eight postdoc fellows in technologies for digital transformation
Digital Futures announces a call for postdoc fellows in technologies for digital transformation Digital Futures announces a Call for postdoc fellowships with a submission deadline on 26 March 2024. Digital Futures postdoc fellowships aim to support talented early career international researchers in pursuing […]
Read moreSensor technology finds leaks and tracks contaminants in drinking water
Researchers at Stockholm University, KTH and RISE are developing sensor technology to address drinking water losses caused by pipe leaks, aiming to reduce resource waste and enhance water management in complex urban networks. Led by Professor Viktoria Fodor, the project, […]
Read moreGia Destouni is elected to the US National Academy of Engineering and leads a groundbreaking research project on African freshwater systems
Georgia (Gia) Destouni, Digital Futures Faculty, Professor at Stockholm University and Guest Professor at KTH Royal Institute of Technology, has achieved significant recognition for her contributions to water and environmental science and engineering. Gia Destouni currently serves as a Fellow at the Stellenbosch Institute of Advanced Study (STIAS), […]
Read moreAll the way from Canada – meet Digital Futures Scholar in residence, Baris Fidan!
Baris Fidan is a Professor at the University of Waterloo (UW), Canada, in the Department of Mechanical and Mechatronics Engineering Department, with joint appointments at the Departments of Systems Design Engineering and Electrical and Computer Engineering. He received his PhD […]
Read moreInternational conference Innovations for the Blue Planet 2024
The International Conference 2024: Innovations for the Blue Planet is to be held from 23 to 25 April 2024 in Stockholm. The conference is organized and sponsored by WaterCentre@KTH together with Blue Food – Centre for Future Seafood and the […]
Read moreAlex Taylor: What we research and how we go about doing research is intimately connected!
Alex Taylor is a Reader in Design Informatics at the University of Edinburgh. He has been contributing to the areas of Science and Technology Studies and Human-Computer Interaction for over twenty years and has held positions in both academic and […]
Read moreAI can detect infection before it’s too late!
Researchers from KTH, in collaboration with Neonatal care at Karolinska University Hospital, have developed an advanced AI system that can detect infections in patients, particularly premature babies, as early as 24 hours before conventional symptoms appear. The project “Explainable Machine Learning […]
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