Advanced School for Computing and Imaging (ASCI)

ASCI office
Delft University of Technology
Building 28, room 04.E120
Van Mourik Broekmanweg 6
2628 XE – DELFT, The Netherlands

P: +31 15 27 88032

Visiting hours office
Monday, Tuesday, Thursday: 10:00 – 15:00


The ASCI office is located at the Delft University of Technology campus.  It is easily accessible by bicycle, public transport and car. The numbers of buildings can help you find your way around the campus. Make sure you remember the name and building number of your destination.

Contact us at +31 15 278 8032 or send us an email at

A17 Visualization and Virtual Reality

A17 - Visualization

Year  expected in 2025
Registration  click here
Course content
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 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 maximum number of participants is 20.
Course objectives
The course aims to provide a broad overview of data visualization and to engage students via hands-on exercises.
Education method
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.Provisional structure / format
9:30-12:30 Introductory lectures
12:30-13:30 Lunch
13:30-17:30 Introductory lecturesTuesday – 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 Discussions
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.

Responsible Lecturer

Dr. Fernando V. Paulovich / TUe

Education Period:


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