Contact
Room 404, Engineering Building No.2,
Higher Education Mega-Center,
Guangdong University of Technology
+86 20 3932 2436
find_lab@163.com

WeChat QR Code

We are a branch of the Research Group from Intelligent Information Processing Laboratory.
Learn more about IIP Lab:
www.iiplab.cn
News
  • [Feb. 05]
    The FIND Anunal Metting was held
  • [Oct. 12]
    Maoqiang attended IEEE WCSP 2017 in Nanjing.
  • [Jan. 26]
    The FIND Anunal Metting was held
  • [Jul. 28]
    Maoqiang and Dongdong won the Best Paper Award in ICCC 2016. Congratulations!!
  • [May 17]
    Maoqiang and Dongdong attended IEEE VTC 2016-Spring in Nanjing.
  • [Apr. 18]
    One of our papers on secure vehicular cloud was accepted by IEEE Access.
  • [Apr. 14]
    Two papers were accepted by IEEE CSCloud 2016 and IEEE SSC 2016 respectively.
  • [Apr. 12]
    Dianming He started his visit to Université de Franche-Comté (UFC).
  • [Apr. 09]
    One paper has been accepted for publication in the IEEE Transactions on Vehicular Technology.
  • [Mar. 29]
    New members of class 2016 joined in Find Lab.
  • [Mar. 28]
    Prof. Zhang Yan visited our lab and had a meeting with Ph.D. students.
  • [Mar. 18]
    Dr. Yu will give a talk in WICON 2016 as invited speaker.
  • [Mar. 17]
    Dr. Jiansong Gan from Huawei Tech. visited our lab and gave a talk.
  • [Mar. 12]
    One of our papers ranked No.1 as top popular article in IEEE Network in Jan. 2016.
  • [Mar. 06]
    One paper was accepted by IEEE WCM.
Publications
  • M. Wu, G. Cheng, D. Ye, J. Kang, R. Yu, Y. Wu, and M. Pan, "Federated Split Learning with Data and Label Privacy Preservation in Vehicular Networks", accepted by IEEE Transactions on Vehicular Technology
  • X. Tang, X. Li, R. Yu, Y. Wu, J. Ye, F. Tang, and Q. Cheng, " Digital TwinAssisted Task Assignment in Multi-UAVSystems: A Deep Reinforcement Learning", accepted by IEEE Internet of Things Journal.
  • M. Wu, G. Cheng, P. Li, Y. Wu, and R. Yu, "Split Learning with Differential Privacy for Integrated Terrestrial and Non-Terrestrial Networks", accepted by IEEE Wireless Communications Magazine.
  • P. Li, G. Cheng, X. Huang, J. Kang, R. Yu, Y. Wu, M. Pan, and D. Niyato, "Snowball: Energy Efficient and Accurate Federated Learning with Coarse-to-Fine Compression over Heterogeneous Wireless Edge Devices", accepted by  IEEE Transactions on Wireless Communications.
  • P. Li, Y. Zhong, C. Zhang, Y. Wu, and R. Yu, "FedRelay: Federated Relay Learning for 6G Mobile Edge Intelligence", accepted by IEEE Transactions on Vehicular Technology.
  • X. Wang, Z. Huang, S. Zheng, R. Yu, M. Pan, "The Unpredictability of Digital Twin for Connected Vehicles", accepted by China Communications.
  • D. Shi, Liang Li, M. Wu, M. Shu, R. Yu, M. Pan and Z. Han, "To Talk or to Work: Dynamic Batch Sizes Assisted Time Efficient Federated Learning over Future Mobile Edge Devices", IEEE Transactions on Wireless Communications, July. 2022
  • Z. Li, W. Su, M. Xu, R. Yu, D. Niyato, S. Xie, "Compact Learning Model for Dynamic Off-Chain Routing in Blockchain-Based IoT", IEEE Journal on Selected Areas in Communications , Oct. 2022.
  • X. Huang, Y. Zhong, Y. Wu, P. Li, R. Yu, "Privacy-Preserving Incentive Mechanism for Platoon Assisted Vehicular Edge Computing with Deep Reinforcement Learning", China Communications, vol. 19, no. 7, pp. 294-309, July. 2022.
  • W. Zhong, X. Huang, Y. Wu, R. Yu, J. Kang, "Decentralized Energy Management for Wireless Power Transfer Assisted Platoon Autonomous Driving: A Leader-to-Follower Approach", IEEE Transactions on Green Communications and Networking, April. 2022.
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