电子邮箱：xuyangcs@ustc.edu.cn
个人主页：https://y-xu.github.io/
课题组主页：https://int-ustc.github.io/
主要研究方向：物联网、边缘智能、联邦学习、联邦大模型、AI智能体
许杨，男，安徽寿县人。现为中国科大计算机科学与技术学院副教授，硕士生导师。2014年于武汉理工大学计算机科学与技术学院获学士学位，2019年于中国科学技术大学计算机科学与技术学院获博士学位。2019年荣获中国科大墨子杰出青年特资津贴一等资助，并入选中国科学院特别研究助理资助项目。主要从事物联网、边缘智能计算、AI智能体等方面的研究。近年来，在网络、普适计算、人工智能、数据智能等领域发表高水平论文50余篇，其中一作/通讯论文30余篇（包括MobiCom、UbiComp、ACL、ICDE、INFOCOM、TMC等CCF A类论文35篇），2篇论文入选ESI高被引论文。其中，2016年发表在普适计算领域旗舰会议ACM UbiComp上的论文获最佳论文奖。作为项目负责人主持国自然面上项目、国自然青年项目、江苏省自然青年项目、华为技术咨询项目、北京控制工程研究所横向项目、中国科大青年创新基金等项目各1项；作为技术负责人/项目骨干参与国自然重点项目1项、国家重点研发计划课题1项，以及华为合作项目1项。
获奖情况：
1.2024年，指导的研究生获国家自然科学基金博士生项目（学院仅2名），并入选中国科协青年人才托举工程博士生专项计划
2.2019年，中国科大“墨子杰出青年特资津贴”（一等）
3.2016年，普适计算领域旗舰会议ACM UbiComp最佳论文奖
代表性论著：
[1] Zhiwei Yao, Ji Qi, *Yang Xu, Yunming Liao, Hongli Xu, Lun Wang, PairingFL: Efficient Federated Learning with Model Splitting and Client Pairing, IEEE/ACM Transactions on Networking (ToN), 2025. (CCF A)
[2] Yang Xu, Ying Zhu, Zhiyuan Wang, *Hongli Xu, Yunming Liao. Enhancing Federated Learning through Layer-wise Aggregation over Non-IID Data. Transactions on Services Computing (TSC), 2025. (CCF A)
[3] Yang Xu, Yunming Liao, *Hongli Xu, Zhiyuan Wang, Lun Wang, Jianchun Liu, Chen Qian, FedSNN: Training Slimmable Neural Network with Federated Learning in Edge Computing, IEEE/ACM Transactions on Networking (ToN), 2024. (CCF A)
[4] Yang Xu, Yunming Liao, Lun Wang, *Hongli Xu, Zhida Jiang, Wuyang Zhang, Overcoming Noisy Labels and Non-IID Data in Edge Federated Learning, IEEE Transactions on Mobile Computing (TMC), 2024. (CCF A)
[5] Yunming Liao, *Yang Xu, *Hongli Xu, Zhiwei Yao, Liusheng Huang, Chunming Qiao, ParallelSFL: A Novel Split Federated Learning Framework Tackling Heterogeneity Issues, The 30th Annual International Conference On Mobile Computing And Networking (MobiCom), 2024. (CCF A)
[6] Yunming Liao, *Yang Xu, Hongli Xu, Min Chen, Lun Wang, Chunming Qiao, Asynchronous Decentralized Federated Learning for Heterogeneous Devices IEEE/ACM Transactions on Networking (ToN), 2024. (CCF A)
[7] Suo Chen, *Yang Xu, Hongli Xu, Zhenguo Ma, Zhiyuan Wang, Enhancing Decentralized and Personalized Federated Learning with Topology Construction, IEEE Transactions on Mobile Computing (TMC), 2024. (CCF A)
[8] Zhida Jiang, *Yang Xu, Hongli Xu, Zhiyuan Wang, Jianchun Liu, Chunming Qiao, Semi-Supervised Decentralized Machine Learning with Device-to-Device Cooperation, IEEE Transactions on Mobile Computing (TMC), 2024. (CCF A)
[9] Yunming Liao, *Yang Xu, Hongli Xu, Lun Wang, Zhiwei Yao, Chunming Qiao, MergeSFL: Split Federated Learning with Feature Merging and Batch Size Regulation, IEEE International Conference on Data Engineering (ICDE), 2024 (CCF A)
[10] Zhida Jiang, *Yang Xu, *Hongli Xu, Zhiyuan Wang, Chunming Qiao, Clients Help Clients: Alternating Collaboration for Semi-Supervised Federated Learning, IEEE International Conference on Data Engineering (ICDE), 2024. (CCF A)
[11] Yunming Liao, *Yang Xu, Hongli Xu, Lun Wang, Chen Qian, Chunming Qiao, Decentralized Federated Learning with Adaptive Configuration for Heterogeneous Participants, IEEE Transactions on Mobile Computing (TMC), 2023. (CCF A)
[12] Zhiyuan Wang, Hongli Xu, *Yang Xu, Zhida Jiang, Jianchun Liu, Suo Chen, FAST: Enhancing Federated Learning through Adaptive Data Sampling and Local Training, IEEE Transactions on Parallel and Distributed Systems (TPDS), 2023. (CCF A)
[13] Yang Xu, Zhida Jiang, *Hongli Xu, Zhiyuan Wang, Chen Qian, Chunming Qiao, Liusheng Huang Federated Learning with Client Selection and Gradient Compression in Heterogeneous Edge Systems, IEEE Transactions on Mobile Computing (TMC), 2023. (CCF A)
[14] Yang Xu, Zhenguo Ma, Hongli Xu, Suo Chen, Jianchun Liu, Yinxing Xue, FedLC: Accelerating Asynchronous Federated Learning in Edge Computing, IEEE Transactions on Mobile Computing (TMC), 2023. (CCF A)
[15] Yunming Liao, *Yang Xu, Hongli Xu, Zhiwei Yao, Lun Wang, Chunming Qiao,Accelerating Federated Learning with Data and Model Parallelism in Edge Computing, IEEE/ACM Transactions on Networking (ToN), 2023. (CCF A)
[16] Zhida Jiang, *Yang Xu, Hongli Xu, Lun Wang, Chunming Qiao, Liusheng Huang, Joint Model Pruning and Topology Construction for Accelerating Decentralized Machine Learning, IEEE Transactions on Parallel and Distributed Systems (TPDS), 2023. (CCF A)
[17] Yang Xu, Lun Wang, Hongli Xu, Jianchun Liu, Zhiyuan Wang, Liusheng Huang, Enhancing Federated Learning with Server-Side Unlabeled Data by Adaptive Client and Data Selection, IEEE Transactions on Mobile Computing (TMC), 2023. (CCF A)
[18] Min Chen, *Yang Xu, *Hongli Xu, Liusheng Huang, Enhancing Decentralized Federated Learning for Non-IID Data on Heterogenous Devices, IEEE International Conference on Data Engineering (ICDE), 2023. (CCF A)
[19] Zhenguo Ma, *Yang Xu, Hongli Xu, Jianchun Liu, Yinxing Xue, Like Attracts Like: Personalized Federated Learning in Decentralized Edge Computing, IEEE Transactions on Mobile Computing (TMC), 2022. (CCF A)
[20] Zhida Jiang, *Yang Xu, *Hongli Xu, Zhiyuan Wang, Chen Qian, Heterogeneity-Aware Federated Learning with Adaptive Client Selection and Gradient Compression, INFOCOM 2023. (CCF A)
[21] Yunming Liao, *Yang Xu, Hongli Xu, Lun Wang, Chen Qian, Adaptive Configuration for Heterogeneous Participants in Decentralized Federated Learning, INFOCOM 2023. (CCF A)
[22] Yang Xu, *Wei Yang, Min Chen, Sheng Chen, and Liusheng Huang, Attention-Based Gait Recognition and Walking Direction Estimation in Wi-Fi Networks, IEEE Transactions on Mobile Computing (TMC), 2022. (CCF A)
[23] Suo Chen, *Yang Xu, Hongli Xu, Zhida Jiang, Chunming Qiao, Decentralized Federated Learning with Intermediate Results in Mobile Edge Computing, IEEE Transactions on Mobile Computing (TMC), 2022. (CCF A)
[24] Yang Xu, Yunming Liao, *Hongli Xu, Zhenguo Ma, Lun Wang, Jianchun Liu, Adaptive Control of Local Updating and Model Compression for Efficient Federated Learning, IEEE Transactions on Mobile Computing (TMC), 2022. (CCF A)
[25] Lun Wang, *Yang Xu, Hongli Xu, Min Chen, Liusheng Huang, Accelerating Decentralized Federated Learning in Heterogeneous Edge Computing, IEEE Transactions on Mobile Computing (TMC), 2022. (CCF A)
[26] Jianchun Liu, *Yang Xu, *Hongli Xu, Yunming Liao, Zhiyuan Wang, He Huang, Enhancing Federated Learning with Intelligent Model Migration in Heterogeneous Edge Computing, IEEE International Conference on Data Engineering (ICDE), 2022. (CCF A)
[27] Zhida Jiang, *Yang Xu, *Hongli Xu, Zhiyuan Wang, Chunming Qiao, Yangming Zhao, FedMP: Federated Learning through Adaptive Model Pruning in Heterogeneous Edge Computing, IEEE International Conference on Data Engineering (ICDE), 2022. (CCF A)
[28] Lun Wang, *Yang Xu, Hongli Xu, Jianchun Liu, Zhiyuan Wang, Liusheng Huang, Enhancing Federated Learning with In-Cloud Unlabeled Data, IEEE International Conference on Data Engineering (ICDE), 2022. (CCF A)
【更新于2025年4月】
