Papers
2
Total Citations
52
H-Index
2
About
Zhenni Li is a pioneering researcher at the intersection of social robotics and artificial intelligence, with a primary focus on understanding how humans implicitly perceive and interact with intelligent machines. Her groundbreaking work challenges conventional human-robot interaction (HRI) methodologies by introducing implicit measures of mind perception, moving beyond explicit self-reports to capture the automatic cognitive processes that shape our encounters with social robots. Her highly cited 2022 paper, "Mind the Machines," has garnered 32 citations and is reshaping how researchers study human-robot relationships, revealing that our unconscious beliefs about machine agency profoundly influence interaction quality. Li also makes significant contributions to IoT and localization technologies, as demonstrated by her 2020 work on block-sparse coding for device-free localization (DFL), which has 20 citations and advances dependable target detection without requiring wearable devices—critical for applications in intrusion detection and mobile robot navigation. Her interdisciplinary approach bridges cognitive science and engineering, offering novel frameworks for designing more intuitive and socially aware robotic systems. Li’s work is essential reading for students and researchers exploring the cognitive foundations of human-robot interaction and the future of autonomous systems.
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Top Papers
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