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.
Subsurface Digital Manager and former Visual Intelligence board member Cathrine Tegnander will serve as the elected leader of Visual Intelligence's board.
The Call for Papers and Abstracts for the Northern Lights Deep Learning (NLDL) Conference 2027 is officially announced – with submission deadlines on August 7th and Mid-September 2026 respectively.
The field of Visual Intelligence is continuously transforming. Chief Research Scientist Arnt-Børre Salberg dives deeper into the current trends in the field of visual intelligence as of early 2026.
Generativ kunstig intelligens er imponerende, men ikke alltid så nyttig til å løse industrielle problemer (Norwegian op-ed in digi.no).
Congratulations to Marit Dagny Kristine Jenssen, who successfully defended her PhD thesis at UiT The Arctic University of Norway on April 10th
The NCS model, a seismic foundation model trained on data from the Norwegian data repository for subsurface data, is now available as an open-source model, allowing anyone to download, utilize, and further develop the model.
The Visual Intelligence Annual Report 2025, highlighting the centre's progress, activities, achieved innovations, staff, funding, and publications for 2025, is now available to read on our websites.
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Congratulations to Centre Director Robert Jenssen, who received UiT's Research and Development Award at the university's annual celebration.
Visual Intelligence researchers contributed to the Pioneer Centre for AI workshop on Electronic Health Records research. The aim was to strengthen ties between the two centres on EHR-related research.
Tre av studentene i sivilingeniør i Kunstig Intelligens ved UiT skal delta i NM i KI. Slik gikk det da de ble intervjuet ved hjelp av kunstig intelligens (News article in nordlys.no).
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Rami Al-Belmpeisi is a PhD Research Fellow in the Visual Computing section at DTU Compute, Technical University of Denmark. He visited Visual Intelligence in Tromsø from November 2025 to February 2026.
Visual Intelligence researchers came to the UiT Open Day to inform the students about UiT's study programme, and inspire them to pursue AI-related studies and career paths.
Congratulations to our colleague Michael Kampffmeyer, who received the Fridtjof Nansen Prize for Young Researchers in 2026.
We happily welcome Rahul Baburajan as a new PhD Research Fellow at SFI Visual Intelligence's hub in Tromsø.
Congratulations to our colleague Sarina Thomas, who has been recognized as one of Norway's Top 50 Women in Tech!
Elisabeth Wetzer forsker på hvordan maskiner kan lære å analysere medisinske bilder – og samtidig forstå hva legene faktisk ser etter (Norwegian news article on dagsavisen.no)
Visual Intelligence researchers organized a preparatory course for UiT AI students who are attending this year's Norwegian AI Championship.
We happily welcome Veronica Lachi and Qing Liu as new Associate Professors at SFI Visual Intelligence.
Artur Radzivil is a PhD Research Fellow at Vilnius Gediminas Technical University. He visited Visual Intelligence in Oslo from September to November 2025.
Congratulations to Marius Aasan, who successfully defended his PhD thesis at the University of Oslo on February 10th.