2010.09—2014.06 北京航空航天大学 学士

2014.09—2020.06 中国科学院计算技术研究所 博士

2020.07—2023.09 中国科学院计算技术研究所 特别研究助理 

2023.09—至今    中国科学院计算技术研究所 副研究员

学术论文：

[1] Sheng Sun, Zengqi Zhang, Quyang Pan, Min Liu, Yuwei Wang, Tianliu He, Yali Chen, and Zhiyuan Wu. Staleness-Controlled Asynchronous Federated Learning: Accuracy and Efficiency Tradeoff. IEEE Transactions on Mobile Computing (TMC), 2024. (CCF-A类期刊)

[2] Xujing Li, Sheng Sun, Min Liu, Ju Ren, Xuefeng Jiang, Tianliu He. FedCRAC: Improving Federated Classification Performance on Long-Tailed Data via Classifier Representation Adjustment and Calibration. IEEE Transactions on Mobile Computing (TMC), 2025. (CCF-A类期刊)

[3] Jingjing Xue, Sheng Sun, Min Liu, Qi Li, Ke Xu. Enhancing Federated Learning Robustness using Locally Benignity-Assessable Bayesian Dropout. IEEE Transactions on Information Forensics and Security (TIFS), 2025. (CCF-A类期刊)

[4] Jingjing Xue, Sheng Sun, Min Liu, Yuwei Wang, Zhuotao Liu, Jingyuan Wang. Learnable Sparse Customization for Heterogeneous Federated Learning. IEEE International Conference on Data Engineering (ICDE), 2025. (CCF-A类会议)

[5] Qingxiang Liu, Sheng Sun, Yuxuan Liang, Jingjing Xue, Min Liu. Personalized Federated Learning for Spatio-Temporal Forecasting: A Dual Semantic Alignment-Based Contrastive Approach. Proceedings of the 39th Annual AAAI Conference on Artificial Intelligence (AAAI), 2025. (CCF-A类会议)

[6] Jingjing Xue, Sheng Sun, Min Liu, Yuwei Wang, Xuying Meng, Jingyuan Wang, JunBo Zhang, Ke Xu. Burst-Sensitive Traffic Forecast via Multi-Property Personalized Fusion in Federated Learning. IEEE Transactions on Mobile Computing (TMC), 2025. (CCF-A类期刊)

[7] Zhiyuan Wu, Sheng Sun, Yuwei Wang, Min Liu, Bo Gao, Quyang Pan, Tianliu He, Xuefeng Jiang. “Agglomerative Federated Learning: Empowering Larger Model Training via End-Edge-Cloud Collaboration”, IEEE International Conference on Computer Communications (INFOCOM), 2024. (CCF-A类会议).

[8] Zhiyuan Wu, Sheng Sun, Yuwei Wang, Min Liu, Ke Xu, Wen Wang, Xuefeng Jiang, Bo Gao, Jinda Lu. FedCache: A Knowledge Cache-driven Federated Learning Architecture for Personalized Edge Intelligence. IEEE Transactions on Mobile Computing (TMC), 2024. (CCF-A类期刊)

[9] Zhiyuan Wu, Sheng Sun, Yuwei Wang, Min Liu, Quyang Pan, Xuefeng Jiang, Bo Gao. “FedICT: Federated Multi-task Distillation for Multi-access Edge Computing”, IEEE Transactions on Parallel and Distributed Systems (TPDS), 2023. (CCF-A类期刊)

[10] Yu Yan, Sheng Sun, Zixiang Tang, Teli Liu, Min Liu. Collaborative Stance Detection via Small-Large Language Model Consistency Verification. Proceedings of the 30th International Conference on Database Systems for Advanced Applications (DASFAA), 2025. (CCF-B类会议)

[11] Xuefeng Jiang, Sheng Sun, Jia Li, Jingjing Xue, Runhan Li, Zhiyuan Wu, Gang Xu, Yuwei Wang, Min Liu. Tackling Noisy Clients in Federated Learning with End-to-end Label Correction. Proceedings of the 31st ACM International Conference on Information & Knowledge Management (CIKM), 2024. (CCF-B类会议)

[12] Qingxiang Liu, Sheng Sun, Min Liu, Yuwei Wang, Bo Gao. Online Spatio-Temporal Correlation-Based Federated Learning for Traffic Flow Forecasting. IEEE Transactions on Intelligent Transportation Systems (TITS), 2024. (CCF-B类期刊)

[13] JingjingXue, Min Liu, Sheng Sun, Yuwei Wang, Hui Jiang, Xuefeng Jiang. FedBIAD: Communication- Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout. Proceedings of the International Parallel & Distributed Processing Symposium (IPDPS), 2023. (CCF-B类会议)

[14] Xujing Li, Min Liu, Sheng Sun, Yuwei Wang, Hui Jiang, Xuefeng Jiang. FedTrip: A Resource Efficient Federated Learning Method with Triplet Regularization. Proceedings of the International Parallel & Distributed Processing Symposium (IPDPS), 2023. (CCF-B类会议)

专利及国内外标准：

[15] 发明专利：基于LLaMA大语言模型的智能合约漏洞检测方法和装置，2024-10-30

[16] 发明专利：基于联邦学习的区块链网络层流量异常检测方法和装置，2024-10-30

[17] 发明专利：一种交通流量预测模型的在线联邦学习方法，2024-06-14

[18] 发明专利：一种基于深度神经网络的边缘计算任务的分配方法及装置，2021-06-25

[19] 国际标准：F.DEC-CFL: Technical framework and requirements for device-edge-cloud collaborative federated learning

[20] 国际标准：Technical framework for deep neural network model partition and collaborative execution

1、国家重点研发计划课题：基于区块链的大规模分布式可信智能计算关键技术及应用，2023-12-01—2026-11-30  

2、国家重点研发计划课题：基于时间敏感网络的跨模态实时可靠通信，2021-12-01—2025-11-30

3、国家自然科学基金重点项目：面向无人系统的网络协同理论与技术，2018-01-01—2022-12-31

4、国家自然科学基金面上项目：无人机集群高效鲁棒的联邦学习技术研究，2025-01-01—2028-12-31

5、国家自然科学基金面上项目：边缘智能中的端边设备协同计算方法研究，2021-01-01—2024-12-31

6、华为企业合作项目：MindSpore网络模型与创新合作项目，2020.12—2021.12

[1] 2024年度“CCF科技成果奖”科技进步一等奖

[2] 2023年度中国通信标准化协会科学技术三等奖

[3] 2020年度国际电信联盟（ITU）AI/ML in 5G全球技术挑战赛银奖（全球62个国家911个参赛队排名并列第3）