Machine Learning meets Visualization
May 24th, 10:00
Amphitheater of the Digiteo Moulon Shannon building (660), How to get to there?
The goal of this talk is to shed light on the relation between machine learning (ML) and interactive visualization (Vis). The talk will be organized along three main parts. First, I will talk about *ML for Vis* as a way to fully or partially automatize the visualization design process. This new approach might potentially lead to a fundamental paradigm shift in visualization research and design. The second part will be on *Vis for ML*. Here, I will specifically illustrate how our approach of visual parameter space analysis can help to better understand ML models, such as dimensionality reduction, clustering, and classification models. Finally, I will argue that a close and tight integration of both *ML and Vis* will pave the way towards the future of interactive data analysis and illustrate some of the ideas with case studies.
Michael Sedlmair is a junior professor at the University of Stuttgart, where he works at the intersection of human-computer interaction, visualization, and data analysis. His specific research interests focus on information visualization, interactive machine learning, virtual and augmented reality, as well as the research and evaluation methodologies underlying them. Previously, Michael has worked at Jacobs University Bremen, University of Vienna, University of British Columbia, University of Munich, and the BMW Group Research and Technology. He also holds visiting professor positions at the Vienna University of Technology, and the Shandong University.