Our research is aimed at developing novel methods, techniques, and tools for the engineering of software for building dependable, efficient, and resilient distributed systems, including cloud-based systems, cyber-physical systems, and scientific computing applications, spanning the following research areas:
- Software Architecture, focussing on the design, modeling, and simulation of distributed system architectures including autonomic and self-adaptive systems,
- Systems Benchmarking, focussing on experimental analysis of performance, scalability, energy efficiency, dependability, and resilience properties,
- Cyber Security, focussing the design, testing, and evaluation of adaptive security architectures and homomorphic computing techniques,
- Predictive Data Analytics, focussing on the software engineering of machine learning and artificial intelligence (AI)-based workflows and tools for time series forecasting, anomaly detection, and critical event prediction.
Orthogonal to these research areas, our past and ongoing research projects span the following application and technology domains:
- Cloud computing, virtualization, software-defined data centers,
- IoT and cyber-physical systems in the domains of transportation/logistics, Industry 4.0, and robotics,
- Scientific computing and high-performance data analytics for earth observation and sustainability research,
- Medicine and sports science.
Our research is inspired by the vision of Self-Aware Computing Systems, which are systems designed with built-in model learning and reasoning capabilities enabling autonomic and proactive decision making at run time. The following pages provide an overview of our long-term vision and research agenda as well as industry cooperations: Vision , Industry Cooperations, Awards and Recognitions, Publications.
Spread over these research areas, our research covers the following application domains:
Tag cloud of all publications: