Research

Signal Processing for Wireless Communications

Signal processing algorithms have received a great deal of attention for the design of advanced wireless communication systems. With our research we analyze the limitations of existing signal processing techniques and we develop new solutions that combine both traditional and emerging signal processing methods in order to meet the diverse requirements of present and future wireless communication networks.

Machine Learning for Physical Layer Wireless Communications

Wireless communication technologies are characterized by a massive number of sophisticated interconnected devices, virtual/augmented reality, and internet-of-things. ... [more]

Intelligent Reflecting Surface Systems

While the fifth-generation (5G) wireless network is still being under deployment, researchers all around the world already work on upcoming beyond 5G networks, such as the sixth-generation (6G) wireless network... [more]

Multi-User MIMO Communications

In cellular networks, the spatial degrees of freedom offered by several antennas at the base station allow serving multiple users simultaneously by transferring data to and from the users... [more]

Automotive Safety and Autonomous Driving

Our research interests are primarily in the field of automotive safety. We focus on the safety of several advanced driver assistance systems (ADAS) and highly automated driving functions; especially the safety of these systems when they are implemented using machine learning-based methods....[more]

Quantum Radar

Motivated by the rapid development of quantum computers in recent years and the increasing interest in quantum technologies, also the field of quantum sensing emerged. The goal of this latter research area is to utilize quantum physical effects in the field of sensor technology and sensing techniques and to develop concepts in order to achieve a higher accuracy of the measured quantity compared to classical approaches and to open up new fields of application....[more]

Generative Modeling for Biomedical Applications

Label-free high-throughput digital holographic microscopy is a novel imaging technique developed to aid clinicians and pathologists in their diagnostics of various diseases. It requires little sample preparation, is automated and allows in-vivo diagnostics of a large amount of living cells and live tissue in a very short amount of time...[more]