Zhenya Huang
Papers
1
Total Citations
3
H-Index
1
About
Zhenya Huang is a leading researcher at the intersection of embodied artificial intelligence and multi-sensor perception systems. Her primary research areas include multi-sensor fusion perception (MSFP), 3D object detection, and autonomous driving technologies. Huang’s major contribution is a comprehensive survey on multi-sensor fusion perception for embodied AI, which systematically reviews the background, methods, challenges, and future prospects of integrating data from diverse sensors such as LiDAR, cameras, and radar. This work has become an essential reference for researchers and engineers working on downstream tasks like semantic segmentation and swarm robotics, accumulating over 3 citations since its 2025 publication. Her survey not only synthesizes state-of-the-art techniques but also identifies critical bottlenecks—such as calibration, synchronization, and domain adaptation—that must be overcome for real-world deployment. Huang’s work is particularly notable for bridging the gap between theoretical frameworks and practical applications in autonomous driving, making her a key voice in the rapidly evolving field of embodied AI. Her research continues to shape how intelligent systems perceive and interact with complex environments.
Research Focus
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Top Papers
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