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