Andreas Hinterreiter

Andreas Hinterreiter

I’m a PhD student and Project Assistant in the Visual Data Science Lab. My research focuses on time series visualization and dimensionality reduction in the context of explainable AI. I am especially interested in non-linear embedding techniques.

My PhD is part of a collaboration with Imperial College London. In 2019 and 2020, I spent a year at the Biomedical Image Analysis (BioMedIA) group at Imperial.

I received my Masters degree in Technical Physics at Johannes Kepler University Linz, working on the structural and chemical analysis of surfaces. As I had grown increasingly interested in machine learning, visualization and graphic design, I decided to transition to visualization research for my PhD.



ProjectionPathExplorer screenshot

Andreas Hinterreiter, Christian A. Steinparz, Moritz Schöfl, Holger Stitz, Marc Streit
ProjectionPathExplorer: Exploring Visual Patterns in Projected Decision-Making Paths
ACM Transactions on Interactive Intelligent Systems (TiiS), Special Issue on Interactive Visual Analytics for Making Explainable and Accountable Decisions (to appear), 2020

Peer-Reviewed Journal and Conference Papers

InstanceFlow screenshot

Michael Pühringer, Andreas Hinterreiter, Marc Streit
InstanceFlow: Visualizing the Evolution of Classifier Confusion on the Instance Level
Proceedings of the IEEE Visualization Short Papers, 2020

ConfusionFlow screenshot

Andreas Hinterreiter, Peter Ruch, Holger Stitz, Martin Ennemoser, Jürgen Bernard, Hendrik Strobelt, Marc Streit
ConfusionFlow: A Model-Agnostic Visualization for Temporal Analysis of Classifier Confusion
IEEE Transactions on Visualization and Computer Graphics (Early Access), 2020

Projective Latent Interventions screenshot

Andreas Hinterreiter, Marc Streit, Bernhard Kainz
Projective Latent Interventions for Understanding and Fine-tuning Classifiers
Interpretable and Annotation-Efficient Learning for Medical Image Computing. Proceedings of the 3rd Workshop on Interpretability of Machine Intelligence in Medical Image Computing (iMIMIC 2020), 2020
 Best Paper Award at iMIMIC 2020