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Prof. Dr. Alexandru C. Telea

Department of Information and Computing Sciences, Utrecht University. Find out more about Alexandru.

Visualizing the Black Box of Machine Learning: Challenges and Opportunities

Machine learning (ML) has witnessed tremendous successes in the last decade in classification, regression, and prediction tasks. However, many ML models are used, and sometimes even designed, as black boxes. When such models do not operate properly, their creators do not often know what is the best way to improve them. Moreover, even when operating successfully, users often require to understand how and why they take certain decisions to gain trust therein. We present how information visualization and visual analytics help towards explaining (and improving) ML models. These cover tasks such as understanding high-dimensional datasets; understanding unit specialization during the training of deep learning models; exploring how training samples determine the shape of classification decision boundaries; and helping users annotating samples in semi-supervised active learning scenarios.

portrait telea


Alexandru Telea is a 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 22 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, and EGPGV. 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).

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Prof. Dr. Tamara Munzner

Department of Computer Science, University of British Columbia. Find out more about Tamara.

Keynote title pending

More information will follow in the coming days and weeks.

portrait munzner


Tamara Munzner is a Professor of Computer Science at the University of British Columbia. She holds a PhD from Stanford and has been active in the visualization field for over 30 years. Her longstanding engagement with the IEEE VGTC community includes service as InfoVis and EuroVis Papers Co-Chair, and chair of the VIS Restructuring Committee, the VIS Executive Committees, and the InfoVis Steering Committee. She published the book "Visualization Analysis and Design" in 2014 as the first in the AK Peters Visualization Series (CRC Press), and continues as series editor. She received the IEEE VGTC Visualization Technical Achievement Award in 2015.