Research at the Faculty of Electrical Engineering

Our focus is on application-oriented research—at the Faculty of Electrical Engineering, our institutes, and our technology transfer centers. This is also evident in many research projects, collaborative doctoral programs, and, not least, in the Applied Research master program. Our state-of-the-art laboratories support both teaching and research. This page provides an overview of our diverse research activities.

Laboratories

Discover the laboratories of the Faculty of Electrical Engineering

About the Laboratories

Technical Cooperation Centers and Institutes

Learn more about the faculty's technology transfer centers and institutes

About the Facilities

Research Groups

Learn more about the research groups in the Faculty of Electrical Engineering

About the Research Groups

Research Projects

Browse our research projects and activities

About the Research Projects

Our Future Topics

In all of its research activities, the Faculty of Electrical Engineering focuses on several topics of the future.

NeoMobil at the TTZ Landsberg; Photo: Matthias Leo

Autonomous Systems

At the Landsberg Technology Transfer Center (TTZ) for Data Science and Autonomous Systems, Prof. Dr.-Ing. Carsten Markgraf and his team are conducting research on autonomous driving and the mobility of the future. Both the knowledge and the insights gained are incorporated into the core curriculum of the bachelor programs as well as into the master’s degree programs offered by the faculty.

RoboticsLab

Manufacturing of the Future

The faculty’s expertise in the field of production engineering is also reflected in the specialized tracks offered in its bachelor’s and master programs:

For example, the TTZ Nördlingen Flexible Automation, under the scientific direction of Prof. Dr.-Ing. Florian Kerber, supports companies in the digital transformation of production engineering.

(Collaborative) robotics has long since found its way into production. At the Augsburg campus, Prof. Dr.-Ing. Simon Dietrich, director of the RoboticsLab at the Technical University of Applied Sciences Augsburg, focuses on this topic.

Prof. Dr.-Ing. Christoph Legat makes a significant contribution to the research areas of digital twins and artificial intelligence—both of which are central aspects of future production.

Renewable Energy Laboratory

Energy Transition

Prof. Dr.-Ing. Michael Finkel and Prof. Dr.-Ing. Christine Schwaegerl cover research areas ranging from networks and smart energy to renewable energy at the Faculty of Electrical Engineering.

THA_ired, Image: Colourbox

Communication

At the Institute for Resource-Efficient Data Transmission and Processing (THA_ired), Prof. Dr.-Ing. Reinhard Stolle and his team are developing highly innovative solutions for the rapid transmission, processing, and distribution of electronic data. This work takes place within the framework of publicly and privately funded research and development projects in cooperation with academic partners and leading companies. THA_ired trains its own next generation of researchers through Master of Applied Research projects and collaborative doctoral programs with partner universities.

Medical technology, Photo: adobestock

People and Technology

Whether the focus is on aspects such as collaborative robotics—as in the Creative Engineering (B.A./B.Eng.) program under Prof. Dr. rer. nat. Martina Königbauer, or health and inclusion, as in the Medical Technology (B.Eng.) program under Prof. Dr.-Ing. Christoph Zeuke, the interplay between people and technology is always a central focus at the Faculty of Electrical Engineering.

AI in Electrical Engineering

AI projects have become an integral part of the Faculty of Electrical Engineering. Methods of artificial intelligence are used in many research projects, feasibility studies, and also in teaching and continuing education.  The areas of AI application in electrical engineering range from environmental perception in autonomous vehicles to smart power grids and the identification of component characteristics for highly varied production processes, all the way to assistance systems that can explain their decisions to humans.