Jack van Wijk
The main challenge is to understand needs, strengths, and limitations of people, in such a way that we can develop powerful methods to support them in their exploration of large and complex data sets. Data science is about people, not about data.
Jack van Wijk is full professor in visualization at the Department of Mathematics and Computer Science of Eindhoven University of Technology (TU/e). His current research interests are information visualization and visual analytics. Previously he worked on flow visualization and mathematical visualization. The challenges are enabling people to explore and understand large amounts of abstract data (information visualization) and integrating methods and techniques from statistics, machine learning, and data mining to deal with even larger data sets (visual analytics). Van Wijk’s work spans many aspects of visualization - representation, interaction, evaluation, and methodology - for a wide variety of applications and data types. He is known for his work on hierarchical data and network visualization. With his students, he has developed new techniques for treemaps, exploring large image collections, event data, vessel traffic, and medicine prescriptions. His current focus is on visually explaining the results of automated methods. Useful results have been obtained for dealing with decision trees and models for judging vessel behavior, the next aim is to develop more generic methods.
Jack received his MSc in industrial design engineering in 1982 and a PhD in computer science in 1986, both with honors from Delft University of Technology. After a short period in the software industry, he worked at the Netherlands Energy Research Foundation ECN for ten years. He joined Eindhoven University of Technology in 1998, where he became a full professor of visualization in 2001. He has (co-)authored more than 150 papers in visualization and computer graphics. Jack has been paper co-chair for IEEE Visualization (2003, 2004), IEEE InfoVis (2006, 2007), IEEE VAST 2009, IEEE PacificVis 2010 and EG/IEEE EuroVis (2011, 2016, 2017). In addition, he is co-founder and VP Scientific Affairs of TU/e spinoff MagnaView BV, which transforms complex data into easy to use analytics products. Another start-up based on his group’s work of is SynerScope BV, which offers powerful solutions for obtaining insights into huge amounts of complex combinations of network, text, image, and multivariate data.
Exploring multivariate event sequences using rules, aggregations, and selectionsIEEE Transactions on Visualization and Computer Graphics (2018)
Semantic network traffic analysis using deep packet inspection and visual analytics(2017)
PathONE : from one thousand patients to one cell(2017)
Comparing personal image collections with PICTuReVisComputer Graphics Forum (2017)
Understanding the context of network traffic alerts(2016)
- Law, ethics & entrepreneurship
- Data Entrepreneurship
- Corporate data entrepreneurship and digital transformation
- Deep learning
- Data visualization
- Adviseur, SynerScope BV
- Adviseur, Magnaview BV