Daniel Jönsson
Associate Professor, Head of Unit
Working in the intersection between visualization and machine learning.
Making complex information understandable
Deciphering complex datasets is no easy task. Raw numbers and abstract statistics often fail to capture the essence of data, hindering human comprehension. My work aims to bridge this gap between humans and data through the power of visualization and machine learning. By combining these two fields, I try to find ways of unraveling hidden patterns, extracting valuable insights, and enabling data-driven decision-making.
Publications
2025
Foreword to the special section on visual computing for biology and medicine (VCBM 2023)
Computers & graphics, Vol. 127, Article 104168
(Article in journal)
https://dx.doi.org/10.1016/j.cag.2025.104168
2024
Model-invariant Weight Distribution Descriptors for Visual Exploration of Neural Networks en Masse
EuroVis 2024 - Short Papers
(Conference paper)
https://dx.doi.org/10.2312/evs.20241068
2023
Semantic Hierarchical Exploration of Large Image Datasets
(Conference paper)
https://dx.doi.org/10.2312/evs.20231051
Eurographics Workshop on Visual Computing for Biology and Medicine: Frontmatter
(Conference proceedings (editor))
https://dx.doi.org/10.2312/vcbm.20232019
CDF-Based Importance Sampling and Visualization for Neural Network Training
Eurographics Workshop on Visual Computing for Biology and Medicine
(Conference paper)
https://dx.doi.org/10.2312/vcbm.20231212