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电信物联网— 王迪

2025-04-01

智能科学与工程学院

1. 个人简介

王迪博士毕业于澳门大学,现任暨南大学智能科学与工程学院讲师,主要研究方向为点云深度学习及其在智能感知中的应用。近年来在《Pattern Recognition》《IEEE Robotics and Automation Letters》《Automation in Construction》等国际顶级期刊上发表多篇论文,涵盖自监督点云理解、三维重建等前沿研究。同时担任《Expert Systems with Applications》《Neural Networks》等多个国际期刊审稿人。

王迪博士每年招收数名硕士生,欢迎对视觉感知方向感兴趣、对科研有热情的学生报读。

2. 教育背景

澳门大学机电工程Electromechanical Engineering,博士学位,中国澳门(2020.08-2024.08

香港理工大学电子信息工程(Electronic and Information Engineering,硕士学位,中国香港(2015.08-2016.08

华南理工大学自动化,学士学位,广州(2011.09-2015.06

华南理工大学国际经济与贸易,第二学士学位,广州(2011.09-2015.06

3. 工作经历

暨南大学智能科学与工程学院,讲师(2024.08至今)

香港理工大学研究助理,中国香港(2017.12-2018.12

香港城市大学,研究助理,中国香港(2016.10-2017.11

4. 研究方向

机器视觉点云语义理解、三维重建、多模态数据融合处理

5. 主要成果

Wang D, Tang L, Wang X, et al. Improving deep learning on point cloud by maximizing mutual information across layers[J]. Pattern Recognition, 2022, 131: 108892.

Wang D, Yang Z X*. Self-supervised point cloud understanding via mask transformer and contrastive learning[J]. IEEE Robotics and Automation Letters, 2022, 8(1): 184-191. 

Wang D, Tang L, Zhu L, et al. Mutual information maximization based similarity operation for 3D point cloud completion network[J]. IEEE Signal Processing Letters, 2022, 29: 1217-1221. 

Wang D, Chen J, Zhao D, et al. Monitoring workers' attention and vigilance in construction activities through a wireless and wearable electroencephalography system[J]. Automation in construction, 2017, 82: 122-137.

Wang D, Li H, Chen J. Detecting and measuring construction workers' vigilance through hybrid kinematic-EEG signals[J]. Automation in Construction, 2019, 100: 11-23.

Li H, Wang D, Chen J, et al. Pre-service fatigue screening for construction workers through wearable EEG-based signal spectral analysis[J]. Automation in Construction, 2019, 106: 102851.

Wang D, Yang Z X*. InfoPCT: Mutual information maximization based point cloud transformer[C]//2022 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC). IEEE, 2022: 17-21.

Zhang D, Ye Q, Wang D, et al. Real-Time Location-to-Image Generative Adversarial Networks with Sparse Sensor Data[C]//2023 29th International Conference on Mechatronics and Machine Vision in Practice (M2VIP). IEEE, 2023: 1-6.

6. 通讯地址

广东省珠海市前山路206号暨南大学珠海校区行政楼631519070

E-maildiwang@jnu.edu.cn

 

 


广东省珠海市前山路206号 邮编:519070