Speaker:Prof. Renato Pajarola
(Head of the Visualizion and MultiMedia Lab, Universität Zürich)
Sobol indices and other, more recent quantities of interest are of great aid in sensitivity analysis, uncertainty quantification, and model interpretation. Unfortunately, computing as well as visualizaing such indices is still challenging for high-dimensional systems. We propose the tensor train decomposition (TT) as a unified framework for surrogate modeling and sensitivity analysis of independently distributed variables, and introduce the Sobol tensor train (Sobol TT) data structure, a compressed data format that can quickly and approximately answer sophisticated queries over exponential-sized sets of Sobol indices. Furthermore, we propose a novel visualization tool that leverages this new Sobol TT representation. Our approach efficiently captures the complete global sensitivity information of high-dimensional scalar models, allows interactive aggregation and subselection operations, and we are able to obtain related Sobol indices and other related quantities at low computational cost. In our three-stage visualization, variable sets to be analyzed can be added or removed interactively. Additionally, a novel hourglass-like diagram presents the relative importance for any single variable or combination of input variables with respect to any composition of the rest of the input variables. We showcase our visualization with several example models, whereby we demonstrate the high expressive power and analytical capability made possible with the proposed Sobol TT method.
Speaker:Dr. Alexandra Diehl
(Department of Informatics, University of Zurich)
The communication and early warning of high-impact weather events (HIWE), their associated risks, and recommendations to the general public, constitute a challenging and continued research topic. These challenges are due to the inherent unpredictability of the weather and the difficulties of quantifying its risk and communicating its uncertainties.
In this talk, I will present our latest research on the visual design of efficient visualization tools to communicate, analyze and quantify HIWE impact, and engage citizens in discussing severe weather events through citizens' participatory science and visualization.
I am a postdoctoral researcher in the Multimedia and Visualization group, led by Prof. Dr. Renato Pajarola at the Department of Informatics of the University of Zurich (UZH), Switzerland. I received my Dip. Eng. in Computer Engineering (2005) and my Ph.D. (2016) in Computer Science at the University of Buenos Aires, Argentina. Before my current position, I was a postdoctoral researcher at the Data Visualization and Analysis Group (DBVIS) at the University of Konstanz, Germany. I am also a lecturer, with experience teaching information visualization, visual analytics, and geographic information systems.
I currently perform research on visual analytics, guidelines and best practices for visualization in projects that range from geovisualization, multimedia analytics to environmental sciences. Along the years, I have dedicated strong efforts to the research and development of visual tools for operational weather forecasting and analysis of high-impact weather events. The full list of publications can be found here.
I am very interested in environmental science and animal protection activities, and I am a proud member of the Zurich Bird Protection / BirdLife Zurich and the Swiss Bird Protection/BirdLife Switzerland, as well as the green team of volunteers at ZÜRCHER TIERSCHUTZ.
45 + 10
Host: Eduard Gröller
Institute of Visual Computing & Human-Centered Technology
Favoritenstr. 9-11 / E193-02
Austria - Europe