Peter Danielis

Prof. Dr.-Ing. habil. Peter Danielis holds an Extraordinary Professorship in Parallel Systems at the Institute of Computer Science, University of Rostock. His research focuses on parallel and distributed systems with applications in time-sensitive networking, autonomous underwater vehicles, and industrial IoT. He serves as Deputy Director of the Institute of Computer Science (IFI) and participates in editorial boards for multiple conferences and journals.

His primary research interests span Parallel Systems, Distributed Computing, and Time-Sensitive Networking, with significant contributions to mobile opportunistic networks and real-time communication in industrial settings. Current projects include cooperative navigation of autonomous underwater vehicles (AUVs) and distributed communication networks for IoT applications. His work bridges theoretical research with industrial implementation, particularly in deterministic networking for critical infrastructure.

Analysis of his recent publications (2020-2025) reveals strong emphasis on Time-Sensitive Networking (TSN) for industrial automation, with 7 of 15 recent papers directly addressing TSN scheduling, reliability, and traffic management. Secondary focus areas include Autonomous Underwater Vehicle coordination (3 papers) and Mobile Opportunistic Networks for urban sensing. His methodology combines simulation, protocol design, and real-world validation.

Professional affiliations include membership in the Institute of Electrical and Electronics Engineers (IEEE). He serves as TPC member and editorial board member for various conferences and journals. His teaching portfolio covers High Performance Computing, Operating Systems, and Complex Software Systems.

As Deputy Director of the Institute of Computer Science, he oversees academic operations while maintaining active research leadership. His laboratory work focuses on real-time communication systems and underwater vehicle networks, utilizing simulation frameworks like OMNeT++ for protocol validation. Current research directions include adaptive TSN scheduling and cooperative AUV navigation in dynamic environments.