Scientific Visualization

Photo credits: Thor Balkhed

The group Scientific Visualization is a part of the division for Media and Information Technology (MIT). 

The group activities range from basic research questions to effective solution of visualization problems originating from diverse application areas. This is developing novel analysis, visualization and exploration techniques for a better understanding and communication of large data.

The applications include fluid-flow simulations, molecular dynamics, digital pathology, material sciences, astronomy, space missions and many medical topics. We develop methods for rendering, analysis and exploration of complex data including scalar, vector and tensor fields.

The research builds on ideas and methods from different areas of computer sciences and mathematics, such as computer graphics, computer vision, dynamical systems, computational geometry, and combinatorial topology.

Research areas

  • Molecular visualization
  • Visualization in medicine
  • Interactive volume rendering
  • Digital Pathology
  • Astronomy visualization
  • OpenSpace: Visualization of space missions 
  • Flow visualization in engineering and medicine
  • Topological methods for data analysis
  • Tensor field visualization
  • Software Inviwo – an extensible, multi-purpose visualization framework

Latest publications


Gabriel Eilertsen, Daniel Jönsson, Jonas Unger, Anders Ynnerman (2024) Model-invariant Weight Distribution Descriptors for Visual Exploration of Neural Networks en Masse EuroVis 2024 - Short Papers Continue to DOI
Christian Simonsson, Elin Nyman, Peter Gennemark, Peter Gustafsson, Ingrid Hotz, Mattias Ekstedt, Peter Lundberg, Gunnar Cedersund (2024) A unified framework for prediction of liver steatosis dynamics in response to different diet and drug interventions Clinical Nutrition, Vol. 43, p. 1532-1543 Continue to DOI
Emilia Ståhlbom, J. Molin, Anders Ynnerman, Claes Lundström (2024) Should I make it round? Suitability of circular and linear layouts for comparative tasks with matrix and connective data Computer graphics forum (Print) Continue to DOI
Danhua Lei, Ehsan Miandji, Jonas Unger, Ingrid Hotz (2024) Sparse q-ball imaging towards efficient visual exploration of HARDI data Computer graphics forum (Print) Continue to DOI
Elias Elmquist, Kajetan Enge, Alexander Rind, Carlo Navarra, Robert Höldrich, Michael Iber, Alexander Bock, Anders Ynnerman, Wolfgang Aigner, Niklas Rönnberg (2024) Parallel Chords: an audio-visual analytics design for parallel coordinates Personal and Ubiquitous Computing Continue to DOI
Bengt Eliasson, Mark E Dieckmann, X Y Jiang, Zheng-Ming Sheng, C S Liu (2024) Role of spontaneous thermal emissionsin inflationary laser Raman instability Physics of Plasmas, Vol. 31, Article 053303 Continue to DOI
Conny Walchshofer, Vaishal Dhanoa, Marc Streit, Miriah Meyer (2024) Transitioning to a Commercial Dashboarding System: Socio-Technical Observations and Opportunities IEEE Transactions on Visualization and Computer Graphics, Vol. 30, p. 381-391 Continue to DOI
S. Sandra Bae, Takanori Fujiwara, Anders Ynnerman, Ellen Yi-Luen Do, Michael L. Rivera, Danielle Albers Szafir (2024) A Computational Design Pipeline to Fabricate Sensing Network Physicalizations IEEE Transactions on Visualization and Computer Graphics, Vol. 30, p. 913-923 Continue to DOI
Milda Poceviciute, Gabriel Eilertsen, Claes Lundström (2024) Benefits of spatial uncertainty aggregation for segmentation in digital pathology Journal of Medical Imaging, Vol. 11 Continue to DOI
Mark E Dieckmann, Lopamudra Palodhi, Conor Fegan, Marco Borghesi (2024) Weibel- and non-resonant Whistler wave growth in an expanding plasma in a 1D simulation geometry Physica Scripta, Vol. 99, Article 045602 Continue to DOI