A Secure Collaborative Spectrum Sensing Strategy in Cyber-Physical Systems. - Hui Lin 007; Jia Hu 001; Jianfeng Ma 001; Li Xu 002; Zhengxin Yu (IEEE Access, 2017)

Federated Learning Based Proactive Content Caching in Edge Computing. - Zhengxin Yu; Jia Hu 001; Geyong Min; Haochuan Lu; Zhiwei Zhao; Haozhe Wang 001; Nektarios Georgalas (GLOBECOM, 2018)

Proactive Content Caching for Internet-of-Vehicles based on Peer-to-Peer Federated Learning. - Zhengxin Yu; Jia Hu 001; Geyong Min; Han Xu; Jed Mills (ICPADS, 2020)

Edge-Computing-Based Channel Allocation for Deadline-Driven IoT Networks. - Weifeng Gao; Zhiwei Zhao; Zhengxin Yu; Geyong Min; Minghang Yang; Wenjie Huang (IEEE Trans. Ind. Informatics, 2020)

Location-Based Robust Beamforming Design for Cellular-Enabled UAV Communications. - Wang Miao; Chunbo Luo; Geyong Min; Yang Mi; Zhengxin Yu (IEEE Internet Things J., 2021)

Mobility-Aware Proactive Edge Caching for Connected Vehicles Using Federated Learning. - Zhengxin Yu; Jia Hu 001; Geyong Min; Zhiwei Zhao; Wang Miao; M. Shamim Hossain (IEEE Trans. Intell. Transp. Syst., 2021)

Intelligent edge caching based on federated deep learning - Zhengxin Yu (2021)

PPFM: An Adaptive and Hierarchical Peer-to-Peer Federated Meta-Learning Framework. - Zhengxin Yu; Yang Lu; Plamen Angelov 001; Neeraj Suri (MSN, 2022)

PINCH: An Adversarial Extraction Attack Framework for Deep Learning Models. - William Hackett; Stefan Trawicki; Zhengxin Yu; Neeraj Suri; Peter Garraghan (CoRR, 2022)

Privacy-Preserving Federated Deep Learning for Cooperative Hierarchical Caching in Fog Computing. - Zhengxin Yu; Jia Hu 001; Geyong Min; Zi Wang 010; Wang Miao; Shancang Li (IEEE Internet Things J., 2022)

Load Prediction in Edge Computing Using Deep Auto-Regressive Recurrent Networks. - Zhanghui Liu; Lixian Chen; Zheyi Chen; Yifan Huang; Jie Liang; Zhengxin Yu; Wang Miao (ICC, 2023)

DNformer: Temporal Link Prediction with Transfer Learning in Dynamic Networks. - Xin Jiang; Zhengxin Yu; Chao Hai; Hongbo Liu 001; Xindong Wu 001; Tomás Ward (ACM Trans. Knowl. Discov. Data, 2023)

Intelligent Offloading in Blockchain-Based Mobile Crowdsensing Using Deep Reinforcement Learning. - Zheyi Chen; Zhengxin Yu (IEEE Commun. Mag., 2023)

Privacy-preserving Decentralized Federated Learning over Time-varying Communication Graph. - Yang Lu; Zhengxin Yu; Neeraj Suri (ACM Trans. Priv. Secur., 2023)

Federated Adversarial Learning for Robust Autonomous Landing Runway Detection. - Yi Li 047; Plamen Angelov 001; Zhengxin Yu; Alvaro Lopez Pellicer; Neeraj Suri (ICANN (6), 2024)

SpreadFGL: Edge-Client Collaborative Federated Graph Learning with Adaptive Neighbor Generation. - Luying Zhong; Yueyang Pi; Zheyi Chen; Zhengxin Yu; Wang Miao; Xing Chen 002; Geyong Min (INFOCOM, 2024)

Computation offloading in blockchain-enabled MCS systems: A scalable deep reinforcement learning approach. - Zheyi Chen; Junjie Zhang 010; Zhiqin Huang; Pengfei Wang; Zhengxin Yu; Wang Miao (Future Gener. Comput. Syst., 2024)

Performance Analytical Modeling of Mobile Edge Computing for Mobile Vehicular Applications: A Worst-Case Perspective. - Wang Miao; Geyong Min; Zhengxin Yu; Xu Zhang 006 (IEEE Trans. Mob. Comput., 2024)

Path Planning for Coverage Spraying of Plants in Outdoor Wheeled Mobile Robots. - Weixin Zhang; Zhengxin Yu; Shixin Mao; Xuefeng Zhou; Jia Pan 001; Haifei Zhu (ICRCA, 2025)

Green Prompting. - Marta Adamska; Daria Smirnova; Hamid Nasiri; Zhengxin Yu; Peter Garraghan (CoRR, 2025)

Game Theory Empowered Carbon-Intelligent Federated Multiedge Caching for Industrial Internet of Things. - Jie Liang; Zhengxin Yu; Haris Pervaiz; Guhan Zheng; Neeraj Suri (IEEE Internet Things J., 2025)

Trust-aware caching-constrained tasks offloading in multi-access edge computing. - Xinyuan Zhu; Fei Hao 001; Ming Lei; Aziz Nasridinov; Jiaxing Shang; Zhengxin Yu; Longjiang Guo (Future Gener. Comput. Syst., 2026)