Longfei Shangguan

Princeton University, Microsoft Research (United Kingdom), Microsoft (United States), University of Pittsburgh

Papers

Total Citations

312

H-Index

About

Longfei Shangguan is a leading researcher at the intersection of mobile computing, robotics, and edge intelligence. His work centers on solving critical challenges in real-time localization, spatial awareness, and autonomous navigation for resource-constrained devices. Shangguan’s most influential contribution is the design of a mobile RFID tag sorting robot (184 citations), which demonstrated how radio-based localization can precisely determine the spatial order of tagged objects—a breakthrough with profound implications for smart libraries, manufacturing, and inventory management. Building on this, he pioneered edge-assisted mobile semantic visual SLAM, a paradigm that offloads computationally intensive visual processing to edge servers, enabling real-time, high-accuracy localization and mapping for robots and autonomous vehicles. His research directly addresses the scalability bottleneck in multi-agent systems, as shown in his recent work on scaling up collaborative visual SLAM for applications like search-and-rescue and industrial inspection. By seamlessly blending edge computing with semantic understanding, Shangguan is shaping the future of autonomous systems that are both intelligent and deployable in the real world.