• April 24, 2026

  • 11:10 AM

  • APB 1004

  • English

Summary

Tensor decompositions have gained much interest in a wide range of disciplines, ranging from natural sciences and engineering to economics and psychometrics as well as machine learning, as powerful tools to cope with challenges around multidimensional and multivariate data. Tensor decompositions can be viewed as a higher-order generalizations of matrix decompositions and are utilized for various data modeling and analysis tasks. In visual computing, computer graphics, image processing or data visualization, it is common to work with multidimensional and multivariate data such as, e.g., in the form of image stacks, volume data, vector/tensor fields, videos, bidirectional texture function (BTF) maps, and more generic multivariate data tables. In this context, tensor decomposition or approximation methods can be explored in particular with respect to compact representation and processing of large-scale or high-dimensional data sets. In this talk we will introduce and focus on the main concepts of tensor decompositions, and review a number of applications to multidimensional and multivariate data visualizations.

Vita

Renato Pajarola Renato Pajarola is a full Professor in the Department of Informatics at the University of Zürich (UZH). He received a Dipl. Inf-Ing ETH as well as a Dr. sc. techn. degree in computer science from the Swiss Federal Institute of Technology (ETH) Zürich in 1994 and 1998 respectively. Subsequently he was a post-doctoral researcher and lecturer in the Graphics, Visualization & Usability Center at Georgia Tech, and in 1999 he joined the University of California Irvine as an Assistant Professor, establishing the Computer Graphics Lab. Since 2005 he has been leading the Visualization and MultiMedia Lab at UZH, and from 2018 to 2022 he was the Chair of the Department of Informatics at UZH. Prof. Pajarola is a Senior Member of ACM and IEEE as well as a Fellow of the Eurographics Association. His research interests include interactive large-scale data visualization, real-time 3D graphics, 3D scanning & reconstruction, geometry processing, as well as remote and parallel rendering. He has published a wide range of internationally peer-reviewed research articles in top journals and conferences.