Dr. Wickstrøm together with his opponents, supervisors and representatives from UiT after his defense.
Kristoffer Wickstrøm defended his PhD thesis “Advancing deep learning with emphasis on data-driven healthcare” on Oct 28 at UiT The Arctic University of Norway.
Kristoffer Wickstrøm defended his PhD thesis “Advancing deep learning with emphasis on data-driven healthcare” on Oct 28 at UiT The Arctic University of Norway.
Wickstrøm has in his thesis developed a range of novel deep learning methods aiming at producing a new level of interpretability and uncertainty quantification for health-related applications within medical computer vision and analysis of patient data from electronic health records.
Wickstrøm defended his work publicly and under the scrutiny of his opponents, Irina Voiculescu, University of Oxford, and Lars Kai Hansen, Technical University of Denmark
Prior to the actual defense, Wickstrøm gave his so-called trial lecture (a requirement in Norway) entitled "Technical aspects of translating AI algorithms into real life medical practice, within the design and implementation of Randomized Controlled Trials".
The right to health is a fundamental human right, but numerous challenges face those who wish to comply. Shortage of trained health personnel, increases in costs, and an aging population are just a few examples of obstacles that arise in the healthcare sector. Tackling such problems is crucial to provide high quality and reliable healthcare to people around the world. Many researchers and healthcare professionals believe that data-driven healthcare has the potential to solve many of of these problems. Data-driven methods are based on algorithms that learn to perform tasks by identifying patterns in data, and often improve in line with the amount of data. A key driving force in contemporary data-driven healthcare is deep learning, which is part of the representation learning field where the goal is to learn a data representation that is beneficial for performing some task. Deep learning has lead to major improvements in important healthcare domains such as computer vision and natural language processing. However, deep learning algorithms lack explainability, do not provide a notion of uncertainty, and struggle when tasked with learning from unlabeled data. These are fundamental limitations that must be tackled for deep learning-based data-driven healthcare to reach its full potential. Towards tackling these limitation, we propose new methodology within the field of deep learning. We present the first methods for capturing uncertainty in explanations of predictions, and we introduce the first framework for explaining representations of data. We also introduce a new method that utilizes domain knowledge to extract clinically relevant features from medical images. While our emphasis is on healthcare applications, the proposed methodology can be employed in other domains as well, and we believe that the innovations in this thesis can play an important part in creating trustworthy deep learning algorithms that can learn from unlabeled data.
The Visual Intelligence Management Team, Robert Jenssen, Line Eikvil, Anne Solberg, and Inger Solheim wish everyone a happy holiday season and new year!
Several of our researchers represented SFI Visual Intelligence at EurIPS 2025 – the NeurIPS-endorsed European AI conference.
Congratulations to Senior Research Scientist Anders Waldeland, who was awarded the Digital Trailblazer Award 2025 at the Dig X Subsurface conference in Oslo, Norway.
Researchers have developed an artificial intelligence that can automatically measure the heart's structure – both quickly and accurately (Popular science article on sciencenorway.no)
Congratulations to Jørgen Agersborg, who successfully defended his PhD thesis at UiT The Arctic University of Norway on November 28th.
State Secretary Marianne Wilhelmsen visited UiT The Arctic University of Norway to learn more about SFI Visual Intelligence and UiT's AI initiatives in education and research.
KI-chatboten Grok har fortalt brukere at verdens rikeste mann er både smartere og sprekere enn noen andre i verden – inkludert basketballstjernen LeBron James og Leonardo da Vinci (Norwegian news article on tv2.no)
Forskere har utviklet kunstig intelligens som automatisk kan måle hjertets struktur – både raskt og presist (Norwegian popular science article on forskning.no)
The Visual Intelligence Graduate School gathered our early career researchers for a 3-Day Science Communication workshop at Skibotn field station outside of Tromsø, Norway.
Onsdag inngikk Aker Nscale og UiT Norges arktiske universitet en ti-årig samarbeidsavtale for å utvikle og styrke kompetansemiljøene for kunstig intelligens i Narvik og Nord-Norge. Aker Nscale garanterer for 100 millioner kroner i avtaleperioden (news story on uit.no)
Centre Director Robert Jenssen and PhD Candidate Lars Uebbing had two fruitful days together with researchers at The Alan Turing Institute's headquarters in London
Centre Director Robert Jenssen represented Visual Intelligence at Outlook North in Harstad, Norway
Senior Research Scientist Anders Waldeland is nominated for the Digital Trailblazer 2025 Award. The winner is announced at the Dig X Subsurface conference in Oslo, Norway in December.
Visual Intelligence researchers have developed an AI to automatically measure the heart's structure – both quickly and accurately. They believe it can help doctors detect and treat cardiovascular diseases faster.
Samuel Kuttner and Elin Kile presented research on PET and artificial intelligence at evening seminar on early detection of prostate cancer organized by the Norwegian Prostate Cancer Assocation.
Centre Director Robert Jenssen represented Visual Intelligence at Svarte Natta 2025 – North Norway's journalist and media conference organized by the Norwegian Union of Journalists.
Congratulations to PhD Candidate Preetraj Bhoodoo, who recently won the Best Poster Presentation Award at the PRESIMAL Autumn Reserach School 2025.
We happily welcome Sigurd Almli Hanssen and Adrian Duric as new PhD Candidates at SFI Visual Intelligence's hubs in Tromsø and Oslo respectively.
AI expert Eirik Agnalt Østmo explains that the law is intended to make AI technology safe for everyone (Popular science article on sciencenorway.no)
Aitor Sánchez is a PhD candidate at the Intelligent Systems Group of the University of the Basque Country in Spain. He visited Visual Intelligence in Tromsø from March to June 2025.