Yi-Jun Zhu

About

Yi-Jun Zhu is a leading researcher in the field of optical wireless communications, with a specific focus on visible light communication (VLC) and its integration with the Industrial Internet of Things (IIoT). His work addresses the critical challenge of enabling simultaneous communication, sensing, and positioning for moving production items like robots and automated guided vehicles (AGVs) in smart factories. Zhu’s major contributions include pioneering the use of deep learning, particularly convolutional neural networks (CNNs), to solve complex problems in VLC. He developed a multi-scale region CNN for visible light sensing that uses shadow features for robust object detection, and a CNN-based method for mobile recognition and positioning across multiple VLC cells. These innovations provide a practical, intelligent solution for real-time environment perception without relying on traditional radio frequency systems. With his highly cited papers accumulating over 10 citations, Zhu’s work is foundational for the next generation of intelligent, vision-enabled IIoT systems, bridging the gap between advanced machine learning and practical optical wireless networks.

Research Focus

Key Achievements

Top Papers

1. 1
   Visible light sensing based on shadow features using multi-scale region convolutional neural network

   6 citations · 2023
2. 2
   Mobile recognition and positioning for multiple visible light communication cells using a convolutional neural network

   4 citations · 2023

Key Collaborators

Contact & Links