Scientific Visualization

Photographer: Thor Balkhed
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

2026

Misgina Tsighe Hagos, Antti Suutala, Dmitrii Bychkov, Hakan Kucukel, Joar von Bahr, Milda Poceviciute, Johan Lundin, Nina Linder, Claes Lundström (2026) Validation of conformal prediction in cervical atypia classification Scientific Reports, Vol. 16, Article 9649 (Article in journal) Continue to DOI
Farhan Rasheed, Abrar Naseer, Talha Bin Masood, Tejas G. Murthy, Vijay Natarajan, Ingrid Hotz (2026) Explorative Analysis of Dynamic Force Networks in 2D Photoelastic Disks Ensembles IEEE Transactions on Visualization and Computer Graphics, Vol. 32, p. 3002-3015 (Article in journal) Continue to DOI
Peilin Yu, Aida Nordman, Takanori Fujiwara, Marta Koc-Januchta, Konrad Schönborn, Lonni Besançon, Katerina Vrotsou (2026) Visual Extraction of Interaction Patterns Guided by Hierarchical Clustering and Process Mining IEEE Transactions on Visualization and Computer Graphics, Vol. 32, p. 1142-1152 (Article in journal) Continue to DOI
Haihan Lin, Maxim Lisnic, Derya Akbaba, Miriah Meyer, Alexander Lex (2026) Heres what you need to know about my data: Exploring Expert Knowledges Role in Data Analysis IEEE Transactions on Visualization and Computer Graphics, Vol. 32, p. 1186-1196 (Article in journal) Continue to DOI
Farhan Rasheed (2026) Topology-Driven Visual Analysis of Structures in Dynamic Spatial Data
Emelie Fälton, Isabelle Strömstedt, Mathis Brossier, Andreas C. Göransson, Konrad Schönborn, Amy Loutfi, Erik Sundén, Mujtaba Fadhil Jawad, Suleiman Yadgar, Johanna Björklund, Mario Romero, Anders Ynnerman, Lonni Besançon (2026) Children's Expectations, Engagement, and Evaluation of an LLM-enabled Spherical Visualization Platform in the Classroom EuroVis 2026 Education Papers (Conference paper)
M. François, Mark E Dieckmann, X. Ribeyre, E. d'Humières (2026) The structure of shocks and contact discontinuities in unmagnetized plasma as a function of the electron-to-proton temperature ratio Physics of Plasmas, Vol. 33, Article 012105 (Article in journal) Continue to DOI

2025

Elmira Zohrevandi, Aida Nordman, Anders Ynnerman, Jonas Lundberg, Carl Westin, Katerina Vrotsou (2025) Engaging Safety-Critical Operators in Visualization Design 2025 IEEE Conference on Engaging Critical Workforce In co-Design aNd Assessment (ECWIDNA), p. 29-33 (Conference paper) Continue to DOI
Omar Mena, Alexandre Kouyoumdjian, Lonni Besançon, Michael Gleicher, Ivan Viola, Anders Ynnerman (2025) Enabling Visually Aware Conversational Data Visualization Through LLM Augmentation SIGGRAPH ASIA 2025 POSTERS, Article 43 (Conference paper) Continue to DOI
Petar Hristov, Ingrid Hotz, Talha Bin Masood (2025) Robust Geometric Predicates for Bivariate Computational Topology 2025 IEEE Workshop on Topological Data Analysis and Visualization (TopoInVis), p. 63-73 (Conference paper) Continue to DOI

Staff

Organisation