Scholar
Rebecka Jörnsten
Google Scholar ID: SO9llAMAAAAJ
Professor of Biostatistics and Applied Statistics, University of Gothenburg, Chalmers
Citations & Impact
Citations
1,380
H-index
17
i10-index
25
Publications
20
Co-authors
25
list available
Publications
Browse publications on Google Scholar (top-right) ↗
Resume (English only)
Academic Achievements
- Published a paper titled 'Reconstructing the regulatory programs underlying the phenotypic plasticity of neural cancers' in Nature Communications; Postdoc Ziming Wang had a paper 'SE(3)-bi-equivariant Transformers for Point Cloud Assembly' accepted at NeurIPS 2024; Received a VR project grant for 'Investigating deep learning through the lens of adaptive kernels'; Participated in the multidisciplinary research center CNSx3: Transformative Models for Brain Diseases.
Research Experience
- She collaborates on multiple research projects, including data integration and joint modeling with Sven Nelander's group; data integration tasks with Mika Gustafsson's group; studying the generalization properties of deep neural networks with Professor Giuseppe Durisi; and merging control theory and neural networks with Balazs Kulcsar.
Background
- Her research focuses on developing new statistical methodologies for neural networks, network modeling, clustering, and model selection, with applications to high-dimensional biological data. Her group consists of students, postdocs, and master's students working on in-house or industry projects.
Miscellany
- Since 2018, she has been the Vice-Dean for Research and Research Infrastructures at the Faculty of Science and Technology, University of Gothenburg, where she chairs the advisory committee, organizes faculty events, and reviews sabbatical applications and faculty prizes.
