Research areas and projects


Research areas and projects


Strategic research areas and associated project


Ongoing projects



We use AI and machine learning to increase accuracy in predictions in a highly complex and ever-changing energy market. 


  • HAWK - Machine learning models for the surveillance of physical power markets | Helge Langseth & Heri Ramampiaro
  • EarlyWarn - Proactive detection and early warning of incipient power system faults | Helge Langseth & Heri Ramampiaro
  • EXAIGON - EXplainable AI systems for Gradual Industry adoptiON | Anastasios Lekkas & Helge Langseth
  • SFI CGF Centre for Geophysical Forecasting | Ole Jakob Mengshoel
  • Machine Learning Algorithms for the Calculation of Water Values | Heri Ramampiaro



connectivity projects

Within the connectivity application area, we work with Internet of Things technology combined with an innovative use of AI. 



oceans projects

We develop and apply AI to ensure a sustainable exploration of maritime sectors, by preventing loss of biodiversity, improving fish welfare in aquaculture and secure fish farms at sea. We also develop robotics for underwater operations.


  • EXPOSED - SFI Centre for Exposed Aquaculture Operations | Helge Langseth, Kerstin Bach & Keith Downing
  • SEAVENTION - Autonomous subsea intervention | Anastasios Lekkas
  • AROS - Autonomous Robots for Ocean Sustainability | Rudolf Mester
  • GentleMAN - Gentle and Advanced Robotic Manipulation of 3D Compliant Objects | Keith Downing
  • PRAI - Predicting Riser-response by Artificial Intelligence | Helge Langseth


health projects

Our projects within health and medicine aim to innovate health technology and improve personalised treaments.


  • selfBACK - A decision support system to facilitate, improve and reinforce self-management of non-specific low back pain | Kerstin Bach
  • Back-UP - Personalised prognostic models to improve well-being and return to work after neck and low back pain | Kerstin Bach
  • InMotion - Prediction of Celebral Palsy in infants | Heri Ramampiaro
  • HiPerNaV - High performance soft tissue navigation | Frank Lindseth
  • Improved cardiac diagnostic imaging at the patients’ point of care | Frank Lindseth & Ole Jakob Mengshoel
  • My Digital Twin | Frank Lindseth
  • SupportPrim - Optimizing management of musculoskeletal pain disorders in primary care | Kerstin Bach
  • SmaRTWork - A digital system for personalised faciliation of the return to work for persons with muscle and skeletal diseases | Kerstin Bach
  • Gemini center MIRA: Medical Imaging Research and AI | Frank Lindseth & Trym Holter


mobility projects

Artificial intelligence is crucial element when developing autonomous vehicles. Our researchers and students work with a variety of vehicles, including cars, ships and drones.

Moreover, we aim to develop AI technology that can contribute to safer and more seamless travel across borders.


  • D4FLY - Detecting Document frauD and iDentity on the fly | Theoharis Theoharis
  • AROS - Autonomous Robots for Ocean Sustainability | Rudolf Mester


digital economy

Our AI research in finance and the digital economy aims to improve predictions of future development in financial and business markets as well improving administration and customer service in banking. 


  • EXAIGON - EXplainable AI systems for Gradual Industry adoptiON | Anastasios Lekkas & Helge Langseth
  • SFI NorwAI - Norwegian Center for Research-based AI Innovation | Jon Atle Gulla, Kjetil Nørvåg, Helge Langseth, Heri Ramampiaro, Kerstin Bach & Ole Jakob Mengshoel


Other application areas & Basic research


Other application areas & basic research


  • SpinENGINE - Harnessing the Emergent Properties of Nanomagnet Ensembles for Massively Parallel Data Analysis | Gunnar Tufte. SpinENGINE is using the emergent and tuneable nonlinear interactions in nanomagnet ensembles as the reservoir to create a new massively parallel, computational device.
  • SOCRATES - Self-Organizing Computational substRATES | Gunnar Tufte. SOCRATES is a long-term time horizon project seeking radical breakthroughs toward efficient and powerful data analysis available everywhere, from the simplest sensor node to the most complex supercomputer.
  • MUSED - Multi-Source Event Detection | Heri Ramampiaro. The MUSED project seeks to solve challenges in event detection and prediction in multi-source data streams in the context of Big Data.
  • ShuttleNet - Scalable Neural Models for Long Sequential Data | Zhirong Yang. In this project we develop a scalable method that enables efficient and accurate inference for very long sequences, up to millions or even billions, of steps.
  • TEFLON - Technology-enhanced foreign and second-language learning of Nordic languages | Giampiero Salvi & Torbjørn Svendsen
  • NordTrans - Technology for automatic speech transcription in selected Nordic languages. Financed by EEA & Norway Grants: KAPPA Programme | Giampiero Salvi & Torbjørn Svendsen