Embedded Systems
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The research area Embedded Systems is inspired by the megatrend of things becoming more intelligent, connected, energy-efficient and sustainable. The growth of artificial intelligence beyond the cloud into the areas of edge computing and thus into embedded systems proves to be an important catalyst for this megatrend.
MAIN AREAS OF RESEARCH
- Innovative system approaches (HW & SW) through interdisiplinary research in the areas of machine learning, signal processing and integrated circuit design
- Intelligent multi-sensor data processing, as well as distributed reasoning, distributed decision-making and automation & control for the development of design methods for ultra-reliable and ultra-scalable systems
- Machine learning for formal methods and formal methods for machine learning - an interdisciplinary approach to reach a new level of reliability for critical embedded software and whole systems
RESEARCH COMPETENCIES
- Neuromorphic architectures and neural networks in HW & SW systems engineering
- Combination of advanced signal processing with machine, deep and reinforcement learning
- Analog, mixed-signal and digital circuit design
- Sensor data processing, sensor fusion and machine perception with machine and deep learning approaches
- Cyber-physical systems and wireless sensor & actuator networks
- Embedded real-time software design
- Embedded HW/SW systems engineering, embedded AI systems, GPU, FPGA and micro controller programming
