姓名：刘建春
电子邮箱：jcliu17@ustc.edu.cn
个人主页：https://jcliu17.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、大模型推理
刘建春，男，安徽省计算机学会优秀青年科学家、CCF互联网专委执行委员、分布式计算与系统专委执行委员。2022年于中国科学技术大学获博士学位，毕业留校任教。现为中国科大计算机学院特任副研究员、硕士生导师。主要从事物联网、边缘智能、联邦学习、大模型训推等方面的研究。近五年，在INFOCOM、SIGKDD、ICDE、ACL等顶级国际会议和ToN、TMC、软件学报、通信学报等国内外著名期刊上发表论文50余篇。其中，以一作/通讯发表CCF A类论文26篇，多篇论文入选ESI高被引论文。申请专利10余项，其中授权专利5项。近年来，作为负责人主持了国家级项目1项、省级项目3项、校级项目1项，以及OPPO、奇瑞企业合作等项目。同时，作为核心技术骨干参与了国自然重点项目、科技部重点研发课题等项目。在科研获奖方面，获得过中科院全国百篇优博、IEEE HITC Outstanding PhD Dissertation Award、CCF网络与数据通信专委优博计划提名、ACM（合肥）优秀博士学位论文、中国科大优秀博士学位论文等荣誉，入选墨子杰出青年特别资助、小米青年学者、华为红专青年人才、苏州独墅湖科教创新区科教骨干人才等。
获奖情况：
1.2026年，墨子杰出青年特别资助
2.2025年，中科院全国百篇优博
3.2024年，IEEE HITC Outstanding PhD Dissertation Award
4.2024年，CCF网络与数据通信专委优博计划提名
5.2024年，ACF优秀青年科学家
6.2023年，ACM优博（合肥）
代表性著作：
[1] Luyao Gao, *Jianchun Liu, Xichong Zhang, Guoju Gao, Yunming Liao, CoSine: Enhancing LLM Serving via Collaborative and Decoupled Speculative Inference , IEEE International Conference on Computer Communications (INFOCOM), 2026. (CCF A类)
[2] Jianchun Liu, Jiaming yan, Ji Qi, Hongli Xu, Shilong Wang, Chunming Qiao, Liusheng Huang, Adaptive Local Update and Neural Composition for Accelerating Federated Learning in Heterogeneous Edge Networks , IEEE/ACM Transactions on Networking (ToN), 2025. (CCF A类)
[3] Luyao Gao, *Jianchun Liu, *Hongli Xu, Sun Xu, Qianpiao Ma, Liusheng Huang, Accelerating End-Cloud Collaborative Inference via Near Bubble-free Pipeline Optimization , IEEE International Conference on Computer Communications (INFOCOM), 2025. (CCF A类)
[4] Wenyi Liang, *Jianchun Liu, *Hongli Xu, Chunming Qiao, Liusheng Huang, Many Hands Make Light Work: Accelerating Edge Inference via Multi-Client Collaborative Caching , IEEE International Conference on Data Engineering (ICDE), 2025. (CCF A类)
[5] Jianchun Liu, Shilong Wang, Hongli Xu, Yang Xu, Yunming Liao, Jinyang Huang, He Huang, Federated Learning With Experience-Driven Model Migration in Heterogeneous Edge Networks[J]. IEEE/ACM Transactions on Networking, 2024. (CCF A类)
[6] Jianchun Liu, Jun Liu, Hongli Xu, Yunming Liao, Zhiwei Yao, Min Chen, Chen Qian, Enhancing Semi-Supervised Federated Learning with Progressive Training in Heterogeneous Edge Computing[J]. IEEE Transactions on Mobile Computing, 2024. (CCF A类)
[7] Jianchun Liu, Jun Liu, Hongli Xu, Yunming Liao, Zhiwei Yao, Min Chen, Chen Qian, Enhancing Semi-Supervised Federated Learning with Progressive Training in Heterogeneous Edge Computing , IEEE Transactions on Mobile Computing (TMC), 2024. (CCF A类)
[8] Jianchun Liu, Qingmin Zeng, Hongli Xu, Yang Xu, Zhiyuan Wang, He Huang, Adaptive block-wise regularization and knowledge distillation for enhancing federated learning[J]. IEEE/ACM Transactions on Networking, 2023. (CCF A类)
[9] Jianchun Liu, Jiaming Yan, Hongli Xu, Zhiyuan Wang, Jinyang Huang, Yang Xu, Finch: Enhancing federated learning with hierarchical neural architecture search[J]. IEEE Transactions on Mobile Computing, 2023. (CCF A类)
[10]Jianchun Liu, Hongli Xu, Lun Wang, Chen Qian, Jinyang Huang, He Huang. Adaptive asynchronous federated learning in resource-constrained edge computing[J]. IEEE Transactions on Mobile Computing, 2023, 22(2): 674-690. (CCF A类, ESI高被引论文)
[更新于2026年3月]
