When: 20.05.2026 10:00-11:00
Where: HS2, Währinger Straße 29
Guest lecturer: Manuela Waldner
Title: Scalable Visual Exploration of Unstructured Data
Abstract: Exploratory visual analysis (EVA) methods were established in the 1970s and are now ubiquitous and considered to be mature. However, I argue that EVA, as we know it, only works reasonably well for data that is well structured. Dimensionality reduction, which is the method of choice for visualizing (large) unstructured data, commonly leads to unnecessarily complicated, inefficient, and even potentially misleading visualizations. Based on theories of sensemaking and categorization, I will promote EVA ideas that -- in collaboration with AI -- help the user to discover semantics captured by the data and to utilize these semantics so that the user detects the expected and discovers the unexpected.
Short Bio: Manuela Waldner is an associate professor at the Institute of Visual Computing & Human-Centered Technology at TU Wien, Austria. She has a PhD in computer science from Graz University of Technology, Austria. Her main research interest is scalable and interactive data analysis and visualization. She has co-authored papers at journals and venues like IEEE Transactions on Visualization and Computer Graphics or ACM Human Factors in Computing Systems, of which some have been nominated or awarded best paper awards. In 2014, she received a Hertha Firnberg fellowship for highly qualified female scientists by the Austrian Science Fund (FWF). She is involved in projects on human-AI collaboration for data exploration, cultural heritage, and large-scale interactive geographic data visualization.