Oblectives, Thematic Areas and Key Research Areas

The Faculty of Computer Science is an innovative and future-oriented faculty within the Teaching and Research Network of the University of Vienna. It covers not only a large variety of subjects in the core areas of computer science, but also the application of these areas in practice, in particular with regard to the wide range of subjects offered at the University of Vienna. Through the interaction and networking of a variety of expert fields, the Faculty of Computer Science is distinguished with a unique profile of expertise. Interdisciplinary ties exist in the areas:

  • business informatics to economics
  • media informatics to communication science, theatre, film and media studies
  • data science and scientific computing to mathematics, chemistry, biology and economics
  • bioinformatics to mathematics, chemistry, biology
  • computational science to mathematics, chemistry and biology, physics, astronomy, earth sciences, pharmacology
  • medical informatics via networking with medical studies at the Medical University of Vienna

Further interdisciplinary networking exists with law, nursing science, psychology and the Centre for Teacher Education. In addition, the Faculty of Computer Science is collaborating with neurobiology and psycholinguistics to establish and expand activities in the field of neuroscience and cognitive science at the University of Vienna.

The faculty focuses its research activities internationally and actively networks with other universities and research institutions on a national and international basis. The aim is to create a balance between basic research and applied research. Technology transfer enhances sustainable and effective research activities.

Thematic Areas

The Faculty’s strategic research areas are focused on the three themes: Computing, Knowledge, Systems, that have become core areas of great importance.

Thematic Areas of research - Faculty of Computer Science


The principles, methods and technologies of computer science are applied in conjunction with those of information and communication technology (ICT) to resolve problems in other academic disciplines.


The area of knowledge comprises all structures and processes of computer science that make it possible to collect, organise, process, analyse, make available and distribute knowledge in all its shapes and forms, and also permits the generation of new knowledge through processes of learning and cooperation.


In computer science, the term ‘system’ refers to the integrated interconnection of objects or processes that depend on each other, interact or interlink.

Key research areas

Within these three thematic areas, the Faculty of Computer Science has established the following key research areas.

Distributed and Multimedia Systems


Information and communication technology form an integral part of everyday life. Ubiquity has increasingly become a key characteristic of information processing systems, and the resulting new challenges, for instance increasingly complex systems, and the handling of large quantities of data (including multimedia data), have to be met. For this reason, aspects of quality, architectures, data models, visualisation and security of distributed and multimedia systems have been gaining importance in both IT research and in application. The convergence of media and networking technology is expected to increase further, and consequently, a comprehensive, system-oriented view with an interdisciplinary orientation will become even more important. Aspects of human-machine interaction and media perception will be particularly relevant in this context.

The Faculty will meet all these challenges in its key research area of distributed and multimedia systems. On the one hand, technology-oriented questions are studied, for instance the internet of the future, service-oriented systems, cloud computing, cooperative systems, IT-infrastructure for industry 4.0, massively distributed, autonomous system infrastructures for e.g. IoT or blockchain applications, and of the entertainment.On the other hand, there are great research opportunities in the application of these systems and their economic effects.

Advanced Laboratories

The combination of various basic and newly researched technologies makes it possible to demonstrate and prove the feasibility of new solutions by means of prototype systems.

Experimental Environments

The development of experimental applications and their evaluation gives the possibility to support knowledge transfer of technological applications and scientific discovery from science into industry and to permit economic utilisation of these research activities


Algorithms, Software and Computing Technologies

The modelling, analysing, visualising, simulating and optimising of complex processes, data structures and dynamic data streams that occur in nature, science and technology as well as industrial processes continually require new technologies. In order to develop and apply those technologies, the Faculty’s key research area of algorithms, software and computing technologies focuses on basic algorithm and software technologies in computer science as well as in the areas where computer science overlaps with other university-based research activities in the areas of computational science and data science. The corresponding research focuses on the following mutually complementary subareas:

There is a focus on programming principles for various computer architectures, including parallel computers and super computers as well as heterogeneous distributed systems and cloud infrastructures. In the area of methodology and algorithms, the development and adaptation of new algorithmic structures in both numerical and combinatorial areas are of key relevance. As far as the processing of complex data structures and dynamic data streams in bioinformatics, business informatics, natural and social sciences are concerned, new methods in the area of data integration, data mining and machine learning, as well as visual data analysis and human-centred design are of particular interest.


Special fields of application of this key research area include, in particular, the processing of very large data quantities, simulation and computer-aided verification of hardware and software, as well as manifold Internet applications.

Knowledge-Based Methods and Technologies for Digitalisation

The main research emphasis is based on the assumption that the real and digital world will increasingly converge. The research emphasis is primarily concerned with questions that arise out of this transformation process.

In the context of a holistic engineering approach, the research focus lies on concepts such as knowledge, methods and technologies. Digitalisation, as an interconnection of ICT with goods and services (“Internet of Things”), leads to a complex distributed ecosystem which has to be sustained by ever more technically capable information systems. The complexity and diversity of digitalisation topics is being addressed not only by appropriate research approaches, but also by a design-oriented approach which also includes disruptive technologies. Due to these considerations, a structure was defined where the subject areas were combined as Enabling Approaches and where Advanced Laboratories as well as Experimental Environments serve as the prototypical realisation and validation of the developed solutions.

Enabling Approaches

comprise the research and development of approaches, methods and tools in the fields of Business Intelligence, Cloud Models, Experimental and Technology-enhanced Learning, Flexible and Connected Processes, Intelligent and Agile Agents as well as Semantic Technologies.

Advanced Laboratories

Within the framework of design-oriented research, prototypical implementations can be designed, realised and validated using Emergent Technologies. By means of Use Cases it is possible to evaluate the developed models within an Experimental Environment. This provides the opportunity to make the symbiosis of the virtual and real world tangible, which arises out of digitalization.

Experimental Environments

The focus is on practical application of research findings, particularly within these areas: Internet of Things, Cyber-Physical Systems and Factories of the Future.