電子郵箱：xuyangcs@ustc.edu.cn
個人主頁：https://y-xu.github.io/
課題組主頁：https://int-ustc.github.io/
主要研究方向：物聯網、邊緣智能、聯邦學習、聯邦大模型、AI智能體
許楊，男，安徽壽縣人。現為188金宝慱体育版 188滚球网 副教授，碩士生導師。2014年於武漢理工大學188滚球网 獲學士學位，2019年於188bet亚洲体育博彩及真人 獲博士學位。2019年榮獲188金宝慱体育版 墨子傑出青年特資津貼一等資助，並入選中國科學院特別研究助理資助項目。主要從事物聯網、邊緣智能計算、AI智能體等方麵的研究。近年來，在網絡、普適計算、人工智能、數據智能等領域發表高水平論文50餘篇，其中一作/通訊論文30餘篇（包括MobiCom、UbiComp、ACL、ICDE、INFOCOM、TMC等CCF A類論文35篇），2篇論文入選ESI高被引論文。其中，2016年發表在普適計算領域旗艦會議ACM UbiComp上的論文獲最佳論文獎。作為項目負責人主持國自然麵上項目、國自然青年項目、江蘇省自然青年項目、華為技術谘詢項目、北京控製工程研究所橫向項目、188金宝慱体育版 青年創新基金等項目各1項；作為技術負責人/項目骨幹參與國自然重點項目1項、國家重點研發計劃課題1項，以及華為合作項目1項。
獲獎情況：
1.2024年，指導的研究生獲國家自然科學基金博士生項目（學院僅2名），並入選中國科協青年人才托舉工程博士生專項計劃
2.2019年，188金宝慱体育版 “墨子傑出青年特資津貼”（一等）
3.2016年，普適計算領域旗艦會議ACM UbiComp最佳論文獎
代表性論著：
[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)
【更新於2025年4月】
