Keynote Speakers

Alexandru Telea

Utrecht University

Alexandru Telea is Professor of Visual Data Analytics at the Department of Information and Computing Sciences, Utrecht University. He holds a PhD from Eindhoven University and has been active in the visualization field for over 25 years. He has been the program co-chair, general chair, or steering committee member of several conferences and workshops in visualization, including EuroVis, VISSOFT, SoftVis, EGPGV, IVAPP, and SIBGRAPI. His main research interests cover unifying information visualization and scientific visualization, high-dimensional visualization, and visual analytics for machine learning. He is the author of the textbook “Data Visualization: Principles and Practice” (CRC Press, 2014).

Keynote Title: Seeing is Learning in High Dimensions: How Dimensionality Reduction Bridges Machine Learning and Data Visualization

Abstract: Computer vision and machine learning (ML) applications are one of the most prominent generators of large, high-dimensional, and complex datasets. Multidimensional projections (MPs) are the techniques of choice for visually exploring such high-dimensional data. Yet, for a long while, the ML and data visualization fields have developed largely independently of each other. In this talk, I will explore the connections, challenges, and potential synergies between these two fields, showing that they share many unexplored commonalities revolving around MPs. These involve “seeing to learn”, or how to deploy MP techniques to open the black box of ML models, and “learning to see”, or how to use ML to create better MP techniques for visualizing high-dimensional data. Examples will cover how to use ML to measure the quality of MPs, using ML to create significantly faster MPs, and extending MPs to create dense representations of ML models.