Bilde av Wickstrøm, Kristoffer
Bilde av Wickstrøm, Kristoffer
Associate Professor / Machine Learning Department of Physics and Technology kristoffer.k.wickstrom@uit.no +4777623216 Tromsø You can find me here

Kristoffer Wickstrøm


Job description

I am an associate professor at UiT The Arctic University of Norway and the group leader of the UiT Machine Learning Group. My research primarily focuses on deep learning, particularly explainability and learning with limited labels. Additionally, I am involved in various professional roles and collaborations, as well as contributing to the broader machine learning community. Below is a summary of my roles, research interests, and past collaborations:

Current Roles:

  • Associate Professor at UiT The Arctic University of Norway.
  • Group Leader of the UiT Machine Learning Group.
  • Head of study program in applied physics and mathematics.
  • Boardmember of the Norwegian association for image processing and machine learning.

Principal Investigator in:

  • SFI Visual Intelligence.
  • SFF Integreat.

Research Interests:

  • Deep learning.
  • Explainability.
  • Learning with limited labels.
  • Uncertainty modeling.
  • Information theory

See Google Scholar for a list of my publications.
Visit my personal website for more information.


  • Lars Uebbing, Harald Lykke Joakimsen, Siyan Chen, Georgios Leontidis, Kristoffer Wickstrøm, Michael Kampffmeyer et al.:
    NOFE – Neural Operator Function Embedding
    Advances in Neural Information Processing Systems 39 2026 ARKIV
  • Valentina Corbetta, Antonio Portaluri, Muzhen He, Daniël Boeke, Regina Beets-Tan, Veronica Lachi et al.:
    Beyond Clean Test Sets: Spurious Correlations in Medical Vision-language Models and the Role of Concept Supervision | MICCAI 2026 - Open Access
    Lecture Notes in Computer Science 2026 ARKIV
  • Solveig Thrun, Zijun Sun, Suaiba Amina Salahuddin, Kristoffer Wickstrøm, Elisabeth Wetzer, Stine Hansen et al.:
    Longitudinal Multi-View Breast Cancer Risk Prediction
    Lecture Notes in Computer Science (LNCS) 2026 ARKIV
  • Jing Wang, Songhe Feng, Jiacheng Li, Kristoffer Wickstrøm, Michael Kampffmeyer :
    AdaptCMVC++: Robust and Flexible Adaptation to Incremental Views in Continual Multi-view Clustering
    IEEE Transactions on Pattern Analysis and Machine Intelligence 14. July 2026 DOI / ARKIV
  • Anna Emilie Jennow Wedenborg, Kristoffer Wickstrøm, Lars Kai Hansen, Morten Mørup, Teresa Dorszewski :
    Explaining Latent Representations of Neural Networks with Archetypal Analysis
    Proceedings of Machine Learning Research (PMLR) 2026 DOI / ARKIV
  • Eirik Agnalt Østmo, Keyur Radiya, Kristoffer Wickstrøm, Michael Kampffmeyer, Karl Øyvind Mikalsen, Robert Jenssen :
    Liver, vessel, and tumor segmentation from partially labeled CT and multi-label masked learning
    Proceedings of Machine Learning Research (PMLR) 01. January 2026 ARKIV
  • Dina Svendsen Solskinnsbakk, Sigurd Almli Hanssen, Harald Lykke Joakimsen, Vilde Benoni Gjærum, Elisabeth Wetzer, Kristoffer Wickstrøm :
    Reducing Manual Workload in SAR-Based Oil Spill Detection Through Uncertainty-Aware Deep Learning
    Proceedings of Machine Learning Research (PMLR) 01. January 2026 DOI / ARKIV
  • Christian Salomonsen, Luigi T. Luppino, Fredrik Emil Aspheim, Kristoffer Wickstrøm, Elisabeth Wetzer, Michael Kampffmeyer et al.:
    A robust and versatile deep learning model for prediction of the arterial input function in dynamic small animal [18F] FDG PET imaging
    EJNMMI Research 09. March 2026 DOI / ARKIV
  • Corbetta, Valentina, Dijkstra, Floris Six, Beets-Tan, Regina, Kervadec, Hoel, Kristoffer Wickstrøm, Silva, Wilson :
    In-hoc Concept Representations to Regularise Deep Learning in Medical Imaging
    Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops 2025 DOI / ARKIV
  • Bjørn Leth Møller, Sepideh Amiri, Christian Igel, Kristoffer Wickstrøm, Robert Jenssen, Matthias Keicher et al.:
    NEMt: Fast Targeted Explanations for Medical Image Models via Neural Explanation Masks
    Proceedings of Machine Learning Research (PMLR) 2025 DOI / ARKIV
  • Thea Brüsch, Kristoffer Wickstrøm, Mikkel N. Schmidt, Tommy Sonne Alstrøm, Robert Jenssen :
    FreqRISE: Explaining time series using frequency masking
    Proceedings of Machine Learning Research (PMLR) 2025 DOI / ARKIV
  • Thea Brüsch, Kristoffer Wickstrøm, Mikkel N. Schmidt, Robert Jenssen, Tommy Sonne Alstrøm :
    FLEXtime: Filterbank Learning to Explain Time Series
    Communications in Computer and Information Science (CCIS) 14. October 2025 DOI / ARKIV
  • Teresa Dorszewski, Lenka Tětková, Robert Jenssen, Lars Kai Hansen, Kristoffer Knutsen Wickstrøm :
    From Colors to Classes: Emergence of Concepts in Vision Transformers
    Communications in Computer and Information Science (CCIS) 12. October 2025 DOI / ARKIV
  • Jing Wang, Songhe Feng, Kristoffer Wickstrøm, Michael Kampffmeyer :
    AdaptCMVC: Robust Adaption to Incremental Views in Continual Multi-view Clustering
    Computer Vision and Pattern Recognition 2025 DOI / ARKIV
  • Duy Khoi Tran, Van Nhan Nguyen, Kristoffer Wickstrøm, Michael Kampffmeyer :
    WOODWORK: A deep-learning based framework for woodpecker damage detection in powerline inspection
    International Journal of Electrical Power & Energy Systems 01. October 2025 DOI / ARKIV
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Kristoffer Wickstrøm et al.:
    Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
    Lecture Notes in Computer Science (LNCS) 20. September 2025 DOI / ARKIV
  • Kristoffer Wickstrøm, Marina Marie-Claire Höhne, Hedström, Anna :
    From Flexibility to Manipulation: The Slippery Slope of XAI Evaluation | SpringerLink
    Lecture Notes in Computer Science (LNCS) 2025 DOI / ARKIV
  • Kristoffer Wickstrøm, Thea Brüsch, Michael Kampffmeyer, Robert Jenssen :
    REPEAT: Improving Uncertainty Estimation in Representation Learning Explainability | Proceedings of the AAAI Conference on Artificial Intelligence
    Proceedings of the AAAI Conference on Artificial Intelligence 11. April 2025 DOI / ARKIV
  • Lars Uebbing, Harald Lykke Joakimsen, Luigi Tommaso Luppino, Iver Martinsen, Andrew McDonald, Kristoffer Wickstrøm et al.:
    Investigating the Impact of Feature Reduction for Deep Learning-based Seasonal Sea Ice Forecasting
    Proceedings of Machine Learning Research (PMLR) 2025 DOI / ARKIV
  • Ingrid Wester Amundsen, Kristoffer Wickstrøm :
    NRK Radio-intervju om KI og dommedag
    18. September 2026 DOI / ARKIV
  • Ingrid Wester Amundsen, Kristoffer Wickstrøm, Vibeke Os :
    NRK Radio-intervju om KI-dagen på UiT
    01. June 2026 DOI / ARKIV
  • Torkil Stoltz, Kristoffer Wickstrøm :
    NRK-intervju om KI-dagen på UiT
    01. June 2026 DOI / ARKIV
  • Robert Jenssen, Kristoffer Wickstrøm, Anne Kjersti Fahlvik, Cathrine Tegnander, Line Eikvil, Karianne Oldernes Tung et al.:
    Verdien av norsk KI-kompetanse, egne modeller og nasjonal innovasjonskraft?
    13. August 2026 DOI / ARKIV
  • Solveig Thrun, Zijun Sun, Suaiba Amina Salahuddin, Kristoffer Wickstrøm, Elisabeth Wetzer, Stine Hansen et al.:
    Longitudinal Multi-View Breast Cancer Risk Prediction
    25. September 2026 ARKIV
  • Solveig Thrun, Zijun Sun, Suaiba Amina Salahuddin, Kristoffer Wickstrøm, Elisabeth Wetzer, Stine Hansen et al.:
    BCRBench: A Breast Cancer Risk Benchmark
    27. September 2026 ARKIV
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Xin Wang et al.:
    Reconsidering Spatial Alignment for Longitudinal Breast Cancer Risk Prediction
    05. January 2026 ARKIV
  • Kristoffer Wickstrøm :
    Intrinsic Information Theoretic Analysis of ReLU Nets
    2026 ARKIV
  • Kristoffer Wickstrøm :
    AI: What is it, what can it do, and what can it not do?
    2026 ARKIV
  • Kristoffer Wickstrøm :
    Kunstig intelligens og fremtiden for administrative tjenester
    2026 ARKIV
  • Kristoffer Wickstrøm :
    Label-efficient computer vision through few-shot learning
    2026 ARKIV
  • Johan Mylius-Kroken, Kristoffer Wickstrøm :
    Best of Both Worlds: Scientific Computing Across Multiple Languages — A Julia and Python Case Study
    2026 DOI / ARKIV
  • Kristoffer Wickstrøm :
    Kunstig intelligens akkurat nå - og hva det kan bety for universitetsbiblioteker
    2026 ARKIV
  • Siyan Chen, Kristoffer Wickstrøm, Robert Jenssen :
    Evaluating AI-based Weather Forecasting Models for Local Wind Speed Prediction in Northern Norway
    08. June 2026 ARKIV
  • Elisabeth Wetzer, Gregor Decristoforo, Kristoffer Wickstrøm :
    Collaborative Coding and Reproducible Research: A Three-Year Course Retrospective
    09. June 2026 ARKIV
  • Lars Uebbing, Henrik Lykke Joakimsen, Kristoffer Wickstrøm, Michael Kampffmeyer, Sebastien Francois Lefevre, Arnt Børre Salberg et al.:
    NOFE - Neural Operator Function Embedding
    08. October 2025 ARKIV
  • Lars Uebbing, Harald Lykke Joakimsen, Theodor Johannes Line Forgaard, Michael Kampffmeyer, Kristoffer Wickstrøm, Sebastien Francois Lefevre et al.:
    Latent Field Reduction of Earth Observation Foundation Model
    07. December 2025 ARKIV
  • Johan Mylius-Kroken, Elisabeth Wetzer, Ali Ramezani-Kebrya, Robert Jenssen, Kristoffer Wickstrøm :
    geobin: Geometric Binning Estimator
    26. November 2025 ARKIV
  • Christian Salomonsen, Samuel Kuttner, Michael Kampffmeyer, Robert Jenssen, Kristoffer Wickstrøm, Jong Chul Ye et al.:
    Fast Voxel-Wise Kinetic Modeling in Dynamic PET using a Physics-Informed CycleGAN
    07. December 2025 ARKIV
  • Christian Salomonsen, Samuel Kuttner, Michael Kampffmeyer, Robert Jenssen, Kristoffer Wickstrøm, Jong Chul Ye et al.:
    Fast Voxel-Wise Kinetic Modeling in Dynamic PET using a Physics-Informed CycleGAN
    Medical imaging meets Eurips (MedEurIPS) 07. December 2025 DOI / ARKIV
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Xin Wang et al.:
    Reconsidering Spatial Alignment for Longitudinal Breast Cancer Risk Prediction
    07. December 2025 ARKIV
  • Christian Salomonsen, Kristoffer Wickstrøm, Samuel Kuttner, Elisabeth Wetzer :
    Physics-Informed Deep Learning for Improved Input Function Estimation in Motion-Blurred Dynamic [18F]FDG PET Images
    16. October 2025 ARKIV
  • Christian Salomonsen, Kristoffer Wickstrøm, Samuel Kuttner, Elisabeth Wetzer :
    Physics-informed deep learning for improved input function estimation in motion-blurred dynamic [18F]FDG PET images
    24. September 2025 ARKIV
  • Johan Mylius-Kroken, Kristoffer Wickstrøm, Elisabeth Wetzer, Ali Ramezani-Kebrya, Robert Jenssen :
    Can a Convex Partition caused by a CPWL Neural Network be used for Density Estimation?
    National conference on image processing and machine learnin 2025 ARKIV
  • Christian Salomonsen, Kristoffer Wickstrøm, Samuel Kuttner, Elisabeth Wetzer :
    Physics-Informed Deep Learning for Improved Input Function Estimation in Motion-Blurred Dynamic [18F]FDG PET Images
    27. September 2025 ARKIV
  • Lars Uebbing, Harald Lykke Joakimsen, Kristoffer Wickstrøm, Michael Kampffmeyer, Sebastien Francois Lefevre, Arnt Børre Salberg et al.:
    NOFE - Neural Operator Function Embedding
    2025 ARKIV
  • Lars Uebbing, Harald Lykke Joakimsen, Kristoffer Wickstrøm, Michael Kampffmeyer, Sebastien Francois Lefevre, Arnt Børre Salberg et al.:
    NOFE Neural Operator Function Embedding
    2025 DOI / ARKIV
  • Solveig Thrun, Stine Hansen, Zijun Sun, Nele Blum, Suaiba Amina Salahuddin, Kristoffer Wickstrøm et al.:
    Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction
    20. September 2025 ARKIV
  • Simen Strømme, Kristoffer Wickstrøm, Kristoffer Søvik, Geir Lippestad, Johannes Bergh :
    Politiske partier har lansert KI-chatboter
    13. May 2025 DOI / ARKIV
  • Elisabeth Wetzer, Youssef Wally, Artem Galushko, Elisavet Kozyri, Kristoffer Wickstrøm :
    How to Tackle Bias and Protect Privacy in the Age of AI?
    17. September 2025 DOI / ARKIV
  • Christian Salomonsen, Kristoffer Wickstrøm, Elisabeth Wetzer, Samuel Kuttner :
    Physics-Informed Machine Learning for dynamic PET modeling
    2025 ARKIV

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    Research interests

    Deep learning.
    Explainable artificial intelligence
    Uncertainty analysis.
    Medical image analysis.
    Learning with limited labeles.


    Member of research group / centre



    Forskningsparken 1 B277


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