Ying Zhang

Papers

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About

Ying Zhang is a researcher specializing in wireless sensor networks, mobile robotics, and distributed localization algorithms. Her work addresses one of the fundamental challenges in sensor network deployment: enabling devices to accurately determine their own position without relying on GPS or dense infrastructure. Zhang's most notable contribution is her development of the Mobility Assisted MDS-MAP(P) algorithm, introduced in her 2007 paper on mobile sensor network self-localization. This work tackled a critical gap in the field — the failure of existing localization methods in sparse mobile sensor networks — by leveraging multi-dimensional scaling (MDS) techniques to solve the mobile self-localization (MSL) problem. The paper has garnered 32 citations, reflecting its significance to the sensor network research community. Building on this foundation, her 2010 work introduced rigidity-guided localization for mobile robotic sensor networks, combining distance graph modeling with robot odometry data to improve positional accuracy through rigidity testing. This approach demonstrated her ability to bridge theoretical graph-based mathematics with practical robotics applications. Zhang's research has meaningful implications for autonomous systems, environmental monitoring, and search-and-rescue robotics, where reliable self-localization under constrained conditions is essential. Her contributions represent important advances in making sparse, mobile sensor networks both practical and precise.