Torsten Braun
Papers
9
Total Citations
211
H-Index
7
About
Torsten Braun is a leading researcher in wireless networking, edge computing, and intelligent localization systems, with a focus on enabling next-generation mobile and IoT applications. His work bridges the gap between theoretical network design and practical, real-world deployment. Braun’s most impactful contributions include pioneering a beaconless opportunistic routing protocol for efficient video dissemination in mobile multimedia IoT, which has garnered 67 citations. He has also advanced indoor positioning with a particle filter-based reinforcement learning approach (60 citations), a critical enabler for 5G networks and beyond. His research extends to managing chains of application functions over multi-technology edge networks (20 citations) and virtual function placement for 5G traffic steering (12 citations), addressing the ultra-low latency demands of augmented reality, robotics, and drone applications. Additionally, Braun has made notable strides in indoor robotic localization, evolving artificial neural network-based systems that leverage wireless network information for autonomous navigation. With a portfolio spanning from foundational localization algorithms to cutting-edge edge network orchestration, Braun’s work is essential reading for students and researchers exploring the intersection of wireless communications, machine learning, and distributed systems.
Research Focus
Key Achievements
Top Papers
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- 3A real-time robust indoor tracking system in smartphones24 citations · 2017
- 4Managing Chains of Application Functions Over Multi-Technology Edge Networks20 citations · 2021
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