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Institute for Media Informatics

The Institute for Media Informatics offers a comprehensive program in media informatics, covering various aspects of the field.

Research Groups

The institute has several research groups, including:

• Ropinski research group
• Rukzio research group
• Weber research group

Teaching

The institute offers a range of courses, including:

• Lectures
• Seminars (seminars)
• Projects
• Thesis works

Winter semester 2025/2026

The courses offered in the winter semester 2025/2026 include:

• Lecture: Automobile user interfaces and interactive vehicle applications
• Lecture: Computer Vision
• Lecture: Basics of media informatics
• Lecture Interactive Visual Design
• Lecture: User-centered design for interactive systems
• Project 3D Deep Learning
• Advanced Visual Deep Learning project
• Project Design Thinking for Interactive Systems
• Project Interactive Systems I
• Interactive information design project
• Project MI - Human-Computer Interaction
• Project Sketching with Hardware
• Project User-Centered Design for Interactive Systems
• Visual Deep Learning project
• Graduate seminar: media informatics
• Seminar Research Trends in Media Informatics
• Seminar Visual Computing

Archive of Courses

The archive of courses includes:

• Summer semester 2025
• Winter semester 2024/25
• Summer semester 2024
• Winter semester 2023/24
• Summer semester 2023
• Winter semester 2022/23
• Summer semester 2022
• Winter semester 2021/22
• Summer semester 2021
• Winter semester 2020/21
• Summer semester 2020
• Winter semester 2019/20

Lecture Course: Data Visualization, Summer Term 2020

Goals

The goals of the course are to become familiar with the basic concepts and algorithms used in the field of visualization and to be able to visualize abstract and spatial data in a way that enhances our perception of the desired relationships in the underlying data.

Content

The course covers the basics in the areas of Information Visualization (INFOVIS) and Scientific Visualization (SCIVIS), including: -Overview

• The visualization pipeline
• Data structures for spatial data
• Visualization of scalar, vector and tensor fields
• Visualization of multi-parametric data
• Glyph based techniques
• Key aspects of visual perception
• Applications of modern visualization systems

Exercise Lessons

The exercise lessons will be held in parallel to the lecture course.

Lecturer

Prof. Dr. Timo Ropinski

Sessions

The lecture course will be held as 3+1 semester week hours scheme. Every other Friday will be used for lab sessions.

Further Information

More information can be found on the Moodle course and LSF entry.