Photo of Daniel Jönsson

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

Renata G. Raidou, James B. Procter, Christian Hansen, Thomas Hollt, Daniel Jönsson (2025) Foreword to the special section on visual computing for biology and medicine (VCBM 2023) Computers & graphics, Vol. 127, Article 104168 (Article in journal) Continue to DOI

2024

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 (Conference paper) Continue to DOI

2023

Alex Bäuerle, Christian van Onzenoodt, Daniel Jönsson, Timo Ropinski (2023) Semantic Hierarchical Exploration of Large Image Datasets
Christian Hansen, James Procter, Renata G Raidou, Daniel Jönsson, Thomas Höllt (Editorship) (2023) Eurographics Workshop on Visual Computing for Biology and Medicine: Frontmatter
Alex Knutsson, Jakob Unnebäck, Daniel Jönsson, Gabriel Eilertsen (2023) CDF-Based Importance Sampling and Visualization for Neural Network Training Eurographics Workshop on Visual Computing for Biology and Medicine (Conference paper) Continue to DOI

Research

Teaching

Organisation