Kaiwen Zha

Papers

Total Citations

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About

Kaiwen Zha is a researcher advancing the safety and autonomy of unmanned robots operating in human environments. His work focuses on perception and localization, particularly for robots navigating crowded, unpredictable spaces. Zha’s most cited contribution, “CornerRadar” (2022, 35 citations), tackles a critical safety challenge: detecting and localizing people hidden around corners to prevent collisions. This system enables robots to anticipate sudden human appearances, addressing a gap in practical, real-time solutions for dynamic indoor settings like factories, malls, and hotels. By leveraging novel sensing and algorithmic approaches, Zha’s research enhances robot situational awareness, reducing accident risks in human-robot interaction. His work is foundational for deploying autonomous systems in shared spaces, blending robotics, computer vision, and safety engineering. With growing citation impact, Zha’s contributions are shaping how robots perceive and respond to their surroundings, making him a notable voice in the field of embodied AI and safe autonomy.