A17 - Visualization

From: June 24 to 28, 2019

Provisional schedule

A17 Visualization
Date + Location
Date: 2019, June 24 - June 28.
Location:  TU Eindhoven, Eindhoven.
For instructions how to get there, see

Provisional structure / format
9:30-12:30 Introductory lectures
12:30-13:30 Lunch
13:30-17:30 Introductory lectures
Tuesday – Friday
9:30-10:30 Introduction to exercise
10:30-12:30 Exercise
12:30-13:30 Lunch
13:30-16:30 Exercise
16:30-17:30 Discussion
Course contents

This graduate course is intended for Ph.D. students that are interested in data visualization and use it or want to use it for their research. Data visualization aims at providing people insight into large amounts of data using interactive computer graphics by exploiting the unique capabilities of the human visual system to perceive patterns, trends, and outliers. The course aims to provide a broad overview of data visualization and to engage students via hands-on exercises. The first day an overview is provided via a number of lectures, followed by four days in which specific topics are addressed via hands-on exercises.
 The topics are:
•    Information visualization: visualization of abstract data, such as tables, hierarchies, networks, and combinations thereof;
•    Scientific visualization: visualization of data with a geometric component, for instance visualization for medical applications.
•    Hardware acceleration: the use of GPU-shaders to obtain special effects in real-time.
•    (a fourth topic is not confirmed yet.)

Essentially, this course is given for Ph.D. students of the Advanced School for Computing and Imaging (ASCI). External Ph.D. students may also attend after a moderate fee of 500 euro. It is assumed that the student has some background in computer graphics, but not specifically in visualization. The students are expected to work in groups of two on the exercises. When necessary a computer can be provided for running the software at hand. The maximum number of participants is 20. The course will be concluded by a small project. Students are asked to apply insights obtained during the course on their own work, and to report back on that on a day to be scheduled later.
Lecturers Jack van Wijk (TU/e)
Dr. Michel Westenberg (TU/e)
Dr. Andrei Jalba (TU/e)
(Lecturer four is not confirmed yet)



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