Key research areas
The key research areas at the Faculty of Computer Science are specified in the development plan of the University of Vienna.
Algorithms | Data Science | Systems | Human-Centered Computing
These encompass contemporary topics in modern computer science and the associated questions regarding the digital future.
Algorithms
The research area Algorithms deals with the development and analysis ofalgorithms, particularly for networks, which are often modelled as graphs. The focus lies on efficient, scalable and energy-efficient algorithms for applications such as social networks, cloud data centres and AI. Dynamic, distributed and parallel algorithms are being studied, partly in relation to data science and neural networks. Graph-based approaches support new computer architectures and parallel programming models.
Data Science
Data Science explores the extraction of knowledge from data and, due of digital transformation, plays a central role in virtually all academic disciplines. Its applications range from the bio- and life sciences to the humanities. The Faculty of Computer Science at the University of Vienna develops methods for databases, data mining, machine learning and visualisation. There are close links to the research area Algorithms, for example in robust algorithms, text mining and neural data analysis.
- Bioinformatics and Computational Biology (BCB)
- Data Mining and Machine Learning (DM)
- Neuroinformatics (NI)
- Visualization and Data Analysis (VDA)
- Workflow Systems and Technology (WST)
- Multimedia Information Systems (MIS)
- Scientific Computing (SC)
- Theory and Application of Algorithms (TAA)
- Education, Didactics and Entertainment Computing (EDEN)
- Security and Privacy (SEC)
- Software Architecture (SWA)
Systems
The research area Systems analyses approaches, methods and tools for the convergence of the physical and digital worlds. Its focus is the development of intelligent, secure and transparent systems (e.g. explainability, security, privacy) as well as approaches to distributed systems. Topics such as Cloud Computing, Blockchain, Cyber-Physical Systems, the Internet of Things (IoT) and Industry 4.0 are central to this research area. A design-oriented approach addresses disruptive technologies and the complex challenges of digitalisation.
Human-Centered Computing
Human-Centred Computing focuses on people and explores human-computer interfaces, inclusive technologies, user experience and the values-based use of technology. The aim is to improve quality of life, social inclusion and education in the context of digital transformation. There are close links to the research areas Data Science (e.g. visualisation, technology-enhanced learning) and Systems (e.g. usable security, design thinking). Additionally, educational technologies and ethical issues surrounding digitalisation play a central role as well.
Objectives
Computer science as an academic discipline has developed at an extraordinary pace. Its impact and potential applications have expanded drastically. The content and methods of computer science have been influencing all other academic disciplines –not just since the advent of ‘artificial intelligence’ (AI) – and its applications have a wide-ranging impact on all areas of life. Especially regarding AI, computer science plays a leading role in algorithmic methodology and the technologies behind it.
In recent years, our Faculty has made a concerted effort to identify and utilise the opportunities associated with these developments. In doing so, we strive to maintain a balance between basic research and applied research.
Furthermore, our Faculty fulfils its responsibility to provide support across all academic disciplines at the university during the rapid development and increasing application of AI by acting as a point of contact, discussion partner and collaborator on all related matters.
Disciplinary strength (and the resulting visibility) are essential prerequisites for another key objective of our Faculty: Interdisciplinary collaborations within the University of Vienna are systematically established and built upon. In addition, important fundamental aspects of computer science make essential contributions in addressing the major societal challenges of our time.
Building on the Faculty’s existing strengths, the focus primarily lies on:
- Bio- and life sciences (drawing on expertise in our Faculty’s research priorities of Algorithms and Data Science, e.g. in the fields of bioinformatics, neuroinformatics and computational drug design),
- Business, Economics and Statistics (building on expertise in our Faculty’s key research areas of Systems and Data Science, e.g. in the fields of business informatics and security)
Social Sciences and Humanities (building on expertise in our Faculty’s key research areas of Human-Centered Computing and Data Science).