Xuemai Gu
Papers
3
Total Citations
10
H-Index
2
About
Xuemai Gu is a researcher specializing in wireless sensor networks (WSNs) and mobile data gathering optimization, with a particular focus on developing intelligent algorithms for smart city infrastructure. Their work centers on solving complex trajectory planning challenges for mobile elements — including robots, autonomous vehicles, and aircraft — tasked with efficiently collecting data across large-scale sensor deployments. Gu's most significant contributions involve tackling the multiple Traveling Salesman Problem (mTSP) within WSN contexts, designing novel clustering and path optimization algorithms that simultaneously minimize travel distance, balance energy consumption, and reduce data gathering latency. Their 2020 paper on heuristic mobile data gathering via trajectory control, which has garnered 6 citations, demonstrates a sophisticated approach to network partitioning and scheduling for smart city applications. Earlier work from 2018, including the EmCA clustering algorithm and the mTSP-CR data gathering framework, further illustrates their commitment to addressing real-world sensor communication constraints in large-scale network environments. While still building a citation profile, Gu's research addresses genuinely critical challenges at the intersection of robotics, network optimization, and IoT infrastructure — areas that will only grow in importance as smart city deployments expand globally.
Research Focus
Key Achievements
Top Papers
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