Papers
4
Total Citations
136
H-Index
3
About
Jianfei Yang is a leading researcher at the forefront of intelligent sensing and robotics, with key contributions spanning indoor localization, autonomous navigation, and domain adaptation. His most impactful work, "Adversarial Learning-Enabled Automatic WiFi Indoor Radio Map Construction and Adaptation With Mobile Robot" (2020, 116 citations), revolutionized location-based services by introducing a mobile robot that autonomously constructs and updates WiFi fingerprint maps—dramatically reducing the labor and time overhead of traditional methods. This work bridges robotics and wireless sensing, enabling scalable, real-time indoor positioning. Yang also advances pedestrian-aware robotics with "AV-PedAware" (2023), a self-supervised audio-visual fusion system that enhances dynamic pedestrian detection using complementary sensor modalities, critical for safe autonomous navigation. His research extends to continuous video domain adaptation (CVDA), where he develops confidence-attention mechanisms to enable models to adapt to evolving visual environments without retraining—vital for robotic vision and autonomous driving. Through biogeography-based optimization for path planning and novel distillation techniques, Yang consistently pushes the boundaries of how robots perceive, navigate, and adapt to complex, dynamic environments, making his work essential reading for researchers in intelligent systems and embodied AI.
Research Focus
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Top Papers
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