Dressler Falko

Data inizio – Data fine: 09 Maggio 2022 - 06 Giugno 2022
Ente di provenienza: TU Berlin
Dipartimento di destinazione: DET - Dipartimento di Elettronica e Telecomunicazioni
Coordinatore al Politecnico: CARLA FABIANA CHIASSERINI

Falko Dressler is full professor and Chair for Telecommunication Networks at the School of Electrical Engineering and Computer Science, TU Berlin. He received his Ph.D. degree from the Dept. of Computer Science, University of Erlangen
in 2003. Dr. Dressler has been associate editor-in-chief for IEEE Trans. on Mobile Computing and Elsevier Computer Communications as well as an editor for journals such as IEEE/ACM Trans. on Networking, IEEE Trans. on Network
Science and Engineering, Elsevier Ad Hoc Networks, and Elsevier Nano Communication Networks. He has been chairing conferences such as IEEE INFOCOM, ACM MobiSys, ACM MobiHoc, IEEE VNC, IEEE GLOBECOM. He
authored the textbooks Self-Organization in Sensor and Actor Networks published by Wiley & Sons and Vehicular Networking published by Cambridge University Press. He was a IEEE Distinguished Lecturer and ACM Distinguished
Speaker. Dr. Dressler is an IEEE Fellow as well as an ACM Distinguished Member. He is a member of the German National Academy of Science and Engineering. He has been serving on the IEEE COMSOC Conference Council and the
ACM SIGMOBILE Executive Committee. Dr. Dressler’s research objectives include adaptive wireless networking (sub-6GHz, mmWave, visible light, molecular
communication) and wireless-based sensing with applications in ad hoc and sensor networks, the Internet of Things, and Cyber-Physical Systems, with emphasis on novel and innovative concepts for 5G/6G communication systems.
In the field of heterogeneous wireless and mobile systems, he is working on methods ranging from coexistence to collaboration in unlicensed spectrum bands. Here, he is particularly interested in new radio resource and interference
management approaches as well as techniques for self-organization and self-adaptation. He also makes use of RF signals for indoor and outdoor localization. The challenge is the fusion of localization information from diverse sources
such as inertial measurement units (IMU). In this line of research, he is also interested in joint communication and sensing. Going beyond standard sub-6GHz channels, he is working on line of sight communication technologies such as
mmWave)and visible light communication (VLC). Research challenges include the characterization of channels based on empirical measurements to develop realistic simulation models, as well as the design of heterogeneous communication
protocols using VLC and/or mmWave in combination with sub-6GHz. Finally, his research interests include vehicular networking (V2X), intelligent transportation systems, safety systems for
vulnerable road users, machine Learning algorithms like reinforcement learning. In a further step, he is studying transfer learning for training in simulation and using the trained models in real world. Importantly, he participated to develop
multiple Open AI Gym-based toolkits, e.g., ns3gym (network simulation), grGym (software defined radio), and VeinsGym (intelligent transportation systems).