Department Computer Science

Department Computer Science Department Computer Science Department Computer Science Department Computer Science

In addition to its teaching activities at UAS Technikum Wien, the technical content of the four competence centers of the Department of Computer Sciences, i.e. ‘Artificial Intelligence and Data Analytics’, ‘Digital Enterprise and UX’, ‘Software Engineering and DevOps’ and ‘Information Security’, focuses on the research and application of such modern ICT technologies as artificial intelligence (AI), augmented and virtual reality, and blockchain technology. The research and development activities bundled within the ‘Data Driven, Smart and Secure Systems’ focus of research are concerned with, among other things, such interdisciplinary subject areas as ‘Interoperable Systems’, ‘eHealth’, ‘Smart Mobility and Smart Cities’, ‘Cyber Security’ and ‘AI in Applications’, and constitute application-oriented areas of research that revolve around embedding within existing processes and companies.


Head of Department

Sylvia Geyer

FH-Prof. Dr. Sylvia Geyer

Rector UAS Technikum Wien
+43 1 333 40 77-5865
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Competence centers

Data are essential to any form of digitalization within industry and society and it is only possible to exploit their benefits through usages that add value. The ‘Artificial Intelligence and Data Science’ competence center focuses on specialist areas, methods and technologies for collecting, managing and exploiting data:

  • In the area of fundamentals, the department is able to draw on expertise in (a) data modeling, (b) data analysis (statistics, multivariate analysis or causal inference using R, Python and Matlab) and (c) data management, e.g. database systems, NoSQL data silos (Elastic Stack, InfluxDB) and big data infrastructures (Hadoop).
  • These are used to develop methods for (a) data warehousing, (b) data mining and machine learning and (c) knowledge engineering, which, among other things, include the formalisms of machine learning (logic, Bayes, decision trees, clustering, neural networks, etc.).

  • Application areas include (a) data-based decision support (business intelligence), (b) smart data approaches for capturing time-series data (e.g. sensor values) and creating predictive models (e.g. predictive maintenance), and (c) selected areas of AI (including speech processing and image recognition).

The expertise flows into teaching and research at UAS Technikum Wien. Moreover, practical seminars are also offered for on-the-job further training (data engineering, data science) along with basic courses for schools (AI basics for educators, robot programming for students).

Keywords: Data modeling, data analysis, multivariate analysis, causal inference, R, Python, Jupyter notebooks, data management, database systems, NoSQL, data lakes, Hadoop, Spark, Kafka, data warehousing, machine learning, logic, reasoning with uncertainty, decision trees, clustering, neural networks, knowledge engineering, business intelligence, smart data technologies, sensor data analytics, deep learning, computer vision, conversational AI, artificial intelligence

Isabel Dregely FHTW

“There is nothing so useless as doing efficiently that which should not be done at all.” (Peter Drucker)

Digitalization enables us to change our actions. Software can be used to provide comprehensive support for tasks, processes, collaboration and much more. The challenge, however, lies in the detail – well-founded decision-making within the framework of tool selection requires the optimization of processes, the description of tasks and the definition of collaboration. Raising the actual added value of digitalization will only then be possible. The ‘Digital Enterprise and UX’ competence center supports these entrepreneurial digitalization activities while preparing students for the challenges in this environment within the scope of academic education as well as in a variety of special training courses.

The core areas of the competence center therefore include:

  • Business analyses, which cover such topics as business-process surveying and modeling, innovation and innovation management, quality management as well as the selection and implementation of IT solutions,
  • Requirements engineering with the capturing, recording, modeling and coordination of software requirements,
  • Usability engineering and human-centered design as well as the testing of usability at our usability lab, e.g. with play-testing or eye-tracking,
  • Traditional, agile and hybrid project management,
  • IT management, including IT governance and IT controlling,
  • The general selection and introduction of IT solutions,
  • eCommerce/mCommerce, digital marketing, growth hacking, social media management and
  • ERP management, including selection, training and implementation.

David Rückel FHTW

A methodical approach, modern programming techniques, efficient development tools and standards are required for the provision and operation of software applications, solutions and systems to an appropriate quality and in accordance with customer requirements.

This ‘goal-oriented provision and systematic use of principles, methods, concepts, notations and tools for the work-sharing, engineering-based development and application of extensive software systems’ are exactly what constitutes software engineering.

DevOps (development and operations) has become a central term in recent years, describing a modern software culture and practice that aims to combine development and operations into an integrated value chain by applying agile development methods and automation.

Focal points in teaching and research:

  • Software system life cycle
  • Process models, software quality, testing, test automation
  • DevOps
  • Lean, agile, continuous build/integration/delivery, IaaS
  • Software architectures
  • Operating systems, distributed systems, cloud computing, interoperability, blockchains, AR/VR
  • Software design and programming methods
  • Design, modeling
  • High-level programming (procedural, object-oriented, functional)
  • App/web development

Information Security

Data and information are particularly valuable assets – and therefore worth protecting – for companies, organizations, public institutions and private individuals. The exponential growth in the number of threats over recent years and the associated need to implement protective measures have increasingly raised awareness of information security and, among other things, have resulted in ‘Cyber Security’ (alongside ‘AI’) being declared as one of the central strategic issues that need addressing by the IT sector in the European Union.

Systems, processes and internal controls must be designed, analyzed and implemented if data is to be protected from the various threats that it faces. It is only in this way that it will be possible to ensure the availability, integrity and confidentiality of data – whether it is currently being stored, processed or transferred.

Due to the fact that the demands on security constitute a very extensive and complex catalog that ranges from the security of transfer networks, the security of both client and server operating systems, network configuration and organizational guidelines through to security and awareness training for employees, this competence center is very broad, drawing on both internal and external know-how.

Keywords: Information security, network security, GDPR, technical security, organizational security, firewalls, IDS and IPS

Wölfel FHTW