Shiwen Mao
Papers
11
Total Citations
125
H-Index
6
About
Shiwen Mao is a researcher whose work spans robotics networking, autonomous systems, and next-generation wireless communications, with a particular focus on connecting intelligent machines in challenging environments. His earliest and most influential contributions addressed the foundational challenge of enabling robot swarms to communicate reliably across distributed networks, culminating in widely cited architectural frameworks for pervasive robot swarm communication networks (2008, 46 citations) that laid important groundwork for multi-robot coordination. Over time, Mao expanded his research vision toward the frontier of 6G communications, exploring how satellites, UAVs, and mobile edge computing can be orchestrated to support mission-critical robotic operations in remote or disaster-struck areas — work reflected in his Edge Information Hub concept (2024, 22 citations). More recently, his research has embraced deep learning-driven autonomy, including imitation learning for RFID-based robotic inventory, recurrent reinforcement learning for long-horizon tasks, and cross-modal reasoning models for unstructured environments. He has also contributed to practical human-robot interaction through hand signal recognition for IoT agents. Collectively, Mao's research traces a coherent arc from foundational networking architectures to intelligent, connected robotic systems — making his portfolio highly relevant to students working at the intersection of robotics, wireless communications, and artificial intelligence.
Research Focus
Key Achievements
Top Papers
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- 4Task-Oriented Satellite-UAV Networks With Mobile-Edge Computing9 citations · 2023
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