Chenming Jiang

A radar serves as an essential automotive component for environment sensing. It is used to detect the objects, estimate their parameters such as the range, velocity and direction of arrival (DOA), track these parameters and classify these objects. To meet the requirement of future high level drive assistant systems, the radar applied should be with high performance, low complexity and robustness to the mutual interference.

Topics of interest include, but are not limited to, the following:

• Development of the automotive radar with high performance, especially with high DOA resolution/accuracy.
• Mitigation of mutual interferences either through traditional signal processing or using deep-learning based approaches.
• Optimization algorithms such as genetic algorithms, evolutionary algorithms and actor critic methods etc.

Armanious, K.; Jiang, C.; Abdulatif, S.; Küstner, T.; Gatidis, S. & Yang, B.
Unsupervised Medical Image Translation Using Cycle-MedGAN
Proceedings of the IEEE European Signal Processing Conference EUSIPCO 2019, A Coruna, Spain, September 2019
 
Armanious, K.; Jiang, C; Fischer, M; Küstner, T; Nikolaou, K; Gatidis, S; Yang, B.
MedGAN: Medical image translation using GANs
Computerized Medical imaging and Graphics, 2019