The Operating System Group’s objective is to reduce complexity for computing systems. To this end, we research, develop, and use our own microkernel to componentise critical parts of systems. We try to push research and development far enough for our results to be usable by other research groups or as starting points for industrial partners.

In the era of Big Data, data management is one of the core pillars of modern enterprise scale information management systems. Within the Dresden Database Research Group, we are addressing a rich bouquet of topics ranging from data refinement and statistical analytics to system-level optimizations in the context of main-memory database systems.

We are working on all aspects of privacy, protecting the data of users from undue processing, transfering, and storing. In particular, we are active in the areas of network security, secure ICT systems, privacy-preserving data analysis, and surveillance prevention.

We are a team of passionate people who advance distributed and networked systems to improve the lives of people. Our research and teaching focus on scalable, reliable, and secure communication in wired and wireless networks. We design and evaluate networking architectures, algorithms as well as protocols, and conduct Internet measurements and analysis. We are involved in open-source projects and Internet tandardization.

The Systems Engineering Group's main research focus is on dependable systems. We follow a divide and conquer approach to address various kinds of faults and failures that can occur in computers and in distributed systems. We are designing and evaluating mechanisms to deal with individual fault types to facilitate developers to choose and match mechanisms depending on a system's dependability requirements.

Software systems are present in our daily life and require more and more interaction between humans and intelligent systems in the future. With the increasing autonomy of systems the algorithmic decisions get more complex and opaque. With our research, we aim for improving the human-machine collaboration in three aspects: (semi-) autonomous systems should be able to explain their behavior; they should be able to adapt themselves to different contexts and users, and they should be safe and trustworthy.

The focus of the professorship includes the Internet of Things. delay-tolerant networks, energy-efficient distributed architectures and system-supported learning. These topics are deepened in various research projects and are also included in further courses. A general introduction to computer networks is also taught in the basic course.