Martin Reisslein

About

Martin Reisslein is a leading researcher at the intersection of 5G/6G networks, real-time video communication, and networked robotics. His work addresses the critical challenge of enabling ultra-low-latency, reliable connectivity for emerging applications like autonomous driving, industrial automation, and remote robot control. Reisslein’s most impactful contribution is his pioneering measurement study of 5G campus networks (159 citations), which provided the first empirical insights into the performance of private 5G networks for industrial and enterprise settings. He has also made seminal contributions to minimizing end-to-end video latency, coining the “glass-to-glass” and “glass-to-algorithm” delay concepts essential for real-time control systems. His innovative work on Digital Twin platforms for long-distance human-in-the-loop robot control, and on dynamic offloading for Visual SLAM in mobile robotics, demonstrates a consistent focus on enabling intelligent, latency-sensitive systems. With over 40 highly cited papers, Reisslein’s research is foundational for the future of tactile internet, edge computing, and networked autonomous systems.

Research Focus

Key Achievements

Top Papers

1. 1
   5G Campus Networks: A First Measurement Study

   159 citations · 2021
2. 2
   On the Minimization of Glass-to-Glass and Glass-to-Algorithm Delay in Video Communication

   40 citations · 2017
3. 3
   Remote Robot Control with Human-in-the-Loop over Long Distances Using Digital Twins

   32 citations · 2019
4. 4
   DynNetSLAM: Dynamic Visual SLAM Network Offloading

   12 citations · 2022
5. 5
   Circular Frame Buffer to Enhance Map Synchronization in Edge Assisted SLAM

   3 citations · 2023

Key Collaborators

Contact & Links