PeopleofSuperintelligence

Researcher

Robert Jenssen

Robert Jenssen is a machine-learning researcher whose work connects information-theoretic learning, kernel methods and deep learning. In 2018, he coauthored a study of information flow in convolutional networks. UiT opened Visual Intelligence with him as centre leader in January 2021; he joined the Max Planck Institute for Intelligent Systems' Scientific Advisory Committee in December 2024. He coauthored a method for multimodal variational autoencoders and received UiT's Research and Development Award in 2025; the IAPR named him a Fellow in 2026. As of October 2026, he is a professor at UiT, directs Visual Intelligence and the Arctic Institute for AI in Science and Innovation, and holds adjunct appointments at the Pioneer Centre for AI and the Norwegian Computing Center.

Now at
Arctic Institute for AI in Science and Innovation, University of Copenhagen and Norwegian Computing Center
Works
243
Citations
7,066
h-index
41
Badges

Publication numbers from OpenAlex, as of 22 October 2026.

Timeline

  1. 2005

    A Dr. Scient. degree

    In 2005, he earns a Dr. Scient. degree.

  2. 2018

    Information theory for CNNs

    In 2018, he coauthors “Understanding Convolutional Neural Networks with Information Theory: An Initial Exploration.” The paper uses matrix-based Rényi entropy estimators to measure information flow in realistic convolutional neural networks.

  3. January 2021

    Opening Visual Intelligence

    In January 2021, UiT opens Visual Intelligence as a Centre for Research-based Innovation focused on artificial intelligence and image analysis, with Jenssen as its centre leader.

  4. December 2024

    The Max Planck advisory role

    In December 2024, he accepts an invitation to join the Scientific Advisory Committee at the Max Planck Institute for Intelligent Systems. He serves as a professor and centre director of SFI Visual Intelligence.

  5. 2025

    CoDE for multimodal VAEs

    In 2025, he coauthors “Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders.” The paper introduces the consensus of dependent experts (CoDE) to combine single-modality distributions and proposes an evidence lower bound that approximates joint multimodal likelihood.

  6. 2025

    UiT research and development award

    He receives UiT's Research and Development Award in 2025.

  7. 2026

    An IAPR fellowship

    In 2026, the IAPR names him a Fellow for contributions at the intersection of information-theoretic learning, kernel machines and deep learning, and for service to the association.

  8. As of October 2026

    Professor and AI centre director

    As of October 2026, he is a professor in UiT's Machine Learning Group and an adjunct professor at the Pioneer Centre for AI at the University of Copenhagen and at the Norwegian Computing Center. He directs Visual Intelligence and the Arctic Institute for AI in Science and Innovation. His research includes deep learning for image analysis and multimodal learning, along with neural networks, information-theoretic learning and kernel methods.

Career

  1. Since 2023University of CopenhagenAdjunct Professor
  2. Since 2017Norwegian Computing CenterAdjunct Professor
  3. Since 2003UiT The Arctic University of NorwayCentre Leader
  4. NowArctic Institute for AI in Science and InnovationDirector
  5. From 2024Max Planck Institute for Intelligent SystemsMember

From the biography and OpenAlex affiliations (the years of papers that list the organization), so some years are approximate.

Most-cited works

  1. Semantic Segmentation of Small Objects and Modeling of Uncertainty in Urban Remote Sensing Images Using Deep Convolutional Neural Networks2016 · IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · 621 citations
  2. Automatic autonomous vision-based power line inspection: A review of current status and the potential role of deep learning2018 · International Journal of Electrical Power & Energy Systems · 596 citations
  3. Kernel Entropy Component Analysis2009 · IEEE Transactions on Pattern Analysis and Machine Intelligence · 304 citations
  4. Recurrent Neural Networks for Short-Term Load Forecasting2017 · SpringerBriefs in computer science · 280 citations
  5. Reconsidering Representation Alignment for Multi-view Clustering2021 · IEEE Computer Society Conference on Computer Vision and Pattern Recognition · 247 citations

From OpenAlex, as of 21 October 2026.

  1. The United States employs an estimated 48% of people shaping AIIncludes University of Copenhagen. We estimate where the people shaping AI work today, how universities, companies and research institutes split across countries, and how country shares have changed since the 1960s.
  2. More people shaping AI studied at Massachusetts Institute of Technology than at any other institutionIncludes University of Copenhagen. We estimate where the people shaping AI studied and where their careers led. Massachusetts Institute of Technology leads with 467 former students, including 291 recorded doctorates.
  3. The company share of AI researchers’ top papers was 31% in 2020–2024 and 8% in 1970–1974Includes University of Copenhagen. We estimate where the people shaping AI worked when their most-cited papers appeared: the company share was 31% in 2020–2024 and 8% in 1970–1974, and Google led all organizations in 2020–2024.
  4. Google has the highest combined h-index among AI organizationsIncludes University of Copenhagen. We estimate that Google holds the highest combined h-index at 8,016, while universities account for 73% of the deduplicated total across AI organizations.

Colleagues

People with dated positions at the same organization in the same years.

Sources and credits

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  1. KI+Narvik | UiT sa.uit.no. Checked 21 October 2026.
  2. Understanding Convolutional Neural Networks with Information Theory: An Initial Exploration arxiv.org. Checked 21 October 2026.
  3. Visual Intelligence åpnet og klare til å løse viktige samfunnsutfordringer | UiT en.uit.no. Checked 21 October 2026.
  4. Centre director Robert Jenssen joins prestigious scientific advisory committee at leading research institute - SFI Visual Intelligence visual-intelligence.no. Checked 21 October 2026.
  5. Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders arxiv.org. Checked 21 October 2026.
  6. Jenssen, Robert | UiT en.uit.no. Checked 21 October 2026.
  7. Alphabetical List of IAPR Fellows – International Association for Pattern Recognition iapr.org. Checked 21 October 2026.
  8. “AI could become crucial for security in the Arctic and the High North” - Arctic Institute for AI in Science and Innovation arcticinstitute.ai. Checked 21 October 2026.