Hedvig Kjellström
Professor
Details
Researcher
About me
I am a Professor in the Division of Robotics, Perception and Learning, KTH, and also affiliated with Swedish e-Science Research Centre and Max Planck Institute for Intelligent Systems, Germany. A short bio is found here.
My main area of research is Computer Vision, which is a sub-field of AI. In my research I develop computer methods to observe and make inferences and predictions about humans and other animals. As outlined in the Portfolio pages, three partly overlapping themes in my research are Computational Aesthetics, Communicative Behavior and Embodied Artificial Intelligence.
I am an Editor-in-Chief for CVIU and was a Program Chair for CVPR 2025.
I teach in the Bachelor program Engineering Mathematics and in the Master programs Machine Learning, Computer Science and Systems, Control and Robotics at KTH. My current courses are found below.
In my free time I play the double bass in different settings, more info here.
News
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Since 2023 I am part of the AI exhibition at Tekniska museet in Stockholm (in Swedish with English subtitles). I can really recommend a visit to this incredibly exciting museum, crossing science, technology, and art. |
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On December 19, 2024, I took part in the radio show Förmiddag med Louise Epstein and talked about how AI and humans can live together. Here is the espisode (in Swedish). |
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NEW PAPER: Carles Balsells-Rodas, Xavier Sumba, Tanmayee Narendra, Ruibo Tu, Gabriele Schweikert, Hedvig Kjellström, and Yingzhen Li. Causal discovery from conditionally stationary time series. In International Conference on Machine Learning, 2025. |
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NEW PAPER: Ci Li, Yi Yang, Zehang Weng, Elin Hernlund, Silvia Zuffi, and Hedvig Kjellström. Dessie: Disentanglement for articulated 3D horse shape and pose estimation from images. In Asian Conference on Computer Vision, 2024. Videos and code |
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NEW PAPER: Ci Li, Ylva Mellbin, Johanna Krogager, Senya Polikovsky, Martin Holmberg, Nima Ghorbani, Michael J. Black, Hedvig Kjellström, Silvia Zuffi, and Elin Hernlund. The Poses for Equine Research Dataset (PFERD). Nature Scientific Data 11, 497, 2024. Data, videos and code |
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NEW PAPER: Silvia Zuffi, Ylva Mellbin, Ci Li, Markus Hoeschle, Hedvig Kjellström, Senya Polikovsky, Elin Hernlund, and Michael J. Black. VAREN: Very accurate and realistic equine network. In IEEE Conference on Computer Vision and Pattern Recognition, 2024. Videos and code |
Courses
Degree Project in Computer Science and Engineering, Second Cycle (DA231X), examiner
Degree Project in Computer Science and Engineering, Second Cycle (DA239X), examiner
Degree Project in Computer Science and Engineering, Second Cycle (DA250X), examiner
Degree Project in Electrical Engineering, Second Cycle (EA250X), examiner
Degree Project in Electrical Engineering, Second Cycle (EA238X), examiner
Engineering Skills in Engineering Mathematics (SA1006), teacher
Fundamentals of Computer Science for Scientific Computing (DD1328), examiner, course responsible
Multimodal Interaction and Interfaces (DT2140), teacher
Program Integrating Course in Machine Learning (DD2301), teacher