Computer science

Cyber-physical systems

The research group of Cyber-Physical Systems (CPS) addresses the close interactions and feedback loop between the embedded cyber components and the dynamic physical components that involve mechanical components, energy systems, human activities and surrounding environment. Designing CPS involves the consideration of multiple factors such as timing, energy, reliability, dependability and security. We need to bring together the experts from different disciplines to tackle the challenges on large scale analytical modeling and analysis, efficient simulations, model driven synthesis and verification, real-time data analytics and system control, etc.

We focus on various aspects, including:

1. model-based design, synthesis and verification of CPS,
2. CPS dependability, security and privacy,
3. big data analytics for CPS,
4. cross-layer modeling and optimization for CPS, and
5. applications of CPS in smart energy systems and automotive systems, etc.

For smarter systems, the main target of our CPS research is to study the link and the interaction between the information technologies, which provide "smartness", and the physical entities which are the "systems".

Information and software visualisation

The research group Information and Software Visualization, ISOVIS, focuses on the explorative analysis and visualization of typically large and complex information spaces, for example in the life sciences, humanities, or software engineering. Our vision is to attack the big data challenge by a combination of human-centered data analysis and interactive visualization for decision-making.

Interactive visualization and visual analytics enable a more efficient and more reliable analysis of the large and complex information spaces that are collected from smart systems and their environments. As a result, smart systems can be better understood and in consequence also better engineered in order to improve the quality of predicting and controlling their performance and behavior, for instance.

Self-adaptive software systems

The research group AdaptWise studies the engineering of Self-adaptive Software Systems, with a particular focus on providing assurances for the qualities of such systems. Self-adaptation provides a principled way to deal with uncertainties of software systems at runtime, ranging from dynamics in the availability of resources to changes of requirements during operation. Adding self-adaptation capabilities to software systems will enable these systems to deal autonomously with dynamics that are difficult to predict. Hence, these systems can take over tedious tasks that are typically performed by human operators, resulting in smarter systems.

Software technologies

The research group Software Technology Labs studies data intensive technologies. Machine learning and artificial intelligence use (big) data to automate tasks such as reasoning, planning, deciding, and predicting. Scalable computing technologies allow coping with the volume of big data sets and the velocity of big data streams. Software and information analysis considers the IT systems as data and reflects on their quality.

Data intensive technologies are enablers for turning data into information and actionable knowledge that automates the implementation of smarter systems or even generates components of these systems.