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.
Heggeli's primary work tasks involve managing, maintaining and optimizing the GPU cluster at UiT Machine Learning (ML) Group in Tromsø, while serving as an important advising resource for our UiT-based VI researchers.
The company's interest in Visual Intelligence is to utilize new developments in artificial intelligence (AI) to improve and automate interpretations of data, while providing the centre with data, problem formulations, and different forms of guidance.
The presented research is part of a larger collaboration between researchers from UiT The Arctic University of Norway and the University Hospital of North Norway.
Visual Intelligence researchers from UiT Machine Learning Group and the University Hospital of North Norway (UNN) were recently featured in the "Abels Tårn" spin-off show "Den store serien om KI".
While visiting Tromsø, Fua held two talks on the topics of "Deep Uncertainty" and "Deep 3D Surface Meshes" for students and researchers at UiT The Arctic University of Norway.
The report showcases Visual Intelligence's activities, results, staff and funding throughout the past year, serving as a detailed compilation of our researchers' efforts towards further development within the centre's four main innovation areas and solving our four research chall
Kunstig intelligens treffer dårligere på kvinner enn menn. Skjevhet i dataene er hovedutfordringen, mener Suaiba Salahuddin, som peker på tre forbedringsmuligheter.
Visual Intelligence Director Robert Jenssen recently gave an invited talk at the CatchID conference organized in Tromsø from 19th-20th March 2024 by the Norwegian Directorate of Fisheries.
The exclusive Lindau Nobel Laureate Meetings gather 650 distinguished scientists and 30 Nobel Prize winners from across the world and places strict requirements in terms of academic and scientific quality. – A great honor, says associate professor Elisabeth Wetzer.
Director Robert Jenssen gave a talk on the uses and misuses of artificial intelligence for members of the seniors association at UiT The Arctic University of Norway. The UiT seniors association consists of former academic and administrative employees at the university.
Researcher Anders U. Waldeland from The Norwegian Computing Center gave a talk at The Biennial Geophysical Seminar in Kristiansand presenting work from Visual Intelligence on seismic structure search using a neural network trained with self-supervised learning.
State secretary Tomas Norvoll visited Visual Intelligence and was given a tour at the PET center at The University Hospital of North Norway by centre director Robert Jenssen and associate professor Samuel Kuttner to learn more about research and innovation within PET and AI.
We are thrilled to announce that the paper "Interrogating Sea Ice Predictability With Gradients", a collaborative paper between Visual Intelligence, The Alan Turing Institute and the British Antarctic Survey, has been accepted in IEEE Geoscience and Remote Sensing Letters.
We congratulate Srishti Gautam for successfully defending her PhD thesis and achieving the PhD degree in Science at UiT The Arctic University of Norway.
Thank you to all students and invited presenters who participated in the Pitch Day at UiT The Arctic University of Norway.
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We were happy to host a school class from Kongsbakken upper secondary school at UiT Norges arktiske universitet on March 13th.
Visual Intelligence director Robert Jenssen recently met with State Secretary Ellen Rønning-Arnesen of Ministry of Health and Care Services.
Det sier førsteamanuensis Kristoffer Wickstrøm. På NHO Arktis sin årskonferanse i Alta delte han innsikt om KI-potensialet og argumenterte for hvorfor nordnorske bedrifter bør investere i denne teknologien. (Norwegian article).
Congratulations to Visual Intelligence co-director Line Eikvil, who was featured on the Abelia and ODA Network's list of the fifty most influential tech women in Norway!
Artificial intelligence tends to perform worse on women, but why? What can be done to ensure that AI-related technologies work well for everyone?