Papers
15
Total Citations
286
H-Index
6
About
Zhiwen Yu is a multidisciplinary researcher whose work spans the convergence of artificial intelligence, Internet of Things (IoT), robotics, and pervasive computing. His most influential contribution, "Behavioral Biometrics for Continuous Authentication in the Internet-of-Things Era" (2020, 202 citations), established him as a leading voice in AI-driven security, demonstrating how behavioral patterns can replace conventional authentication methods across connected devices. This work reflects his broader commitment to building intelligent, adaptive systems for the IoT landscape. Yu's research portfolio reveals a remarkably diverse technical vision. He has advanced mobile crowd sensing through ontology-based middleware and human-robot collaborative frameworks, developed Doppler radar-based gesture recognition for intuitive human-robot interaction, and tackled real-world autonomous driving challenges with cross-modality multi-object tracking under adverse weather. His recent explorations extend into deep-sea soft robotics and graph neural network-based reinforcement learning for multi-robot task scheduling. His "CrowdTransfer" work further exemplifies his forward-thinking approach to knowledge sharing within AIoT communities. With cumulative citations exceeding 270 across his most prominent publications, Yu's research consistently addresses the gap between theoretical AI methods and practical deployment in complex, real-world environments, making his work essential reading for researchers in intelligent systems and autonomous robotics.
Research Focus
Key Achievements
Top Papers
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- 2Plasticized electrohydraulic robot autopilots in the deep sea14 citations · 2025
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- 10CrowdTransfer: Enabling Crowd Knowledge Transfer in AIoT Community4 citations · 2024