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职称：讲师
直属机构：计算机科学与技术学院（软件学院）
学位：工学博士学位
学历：博士研究生毕业
毕业院校：上海交通大学
毕业专业：计算机科学与技术
通讯地址：
邮编：
电子邮箱：hbliu77@suda.edu.cn
联系电话：
传真：
办公地址：天赐庄校区理工楼303
刘海波，苏州大学优秀青年学者、讲师、硕士生导师，ACM / IEEE / CCF会员，博士毕业于上海交通大学计算机学院。主要从事大小模型端云协同、移动端智能体、轻量化持续学习等方向的研究，致力于面向资源受限环境下大模型的高效部署、持续学习与智能体协同优化等关键技术研究。 近年来，在 IEEE TMC、IEEE TSC、IEEE TII、IEEE INFOCOM、ACM KDD、ACM WWW、ACM MM 等国际高水平期刊会议发表学术论文十余篇，其中以第一作者发表 CCF-A 类论文六篇。主持国家自然科学基金青年基金项目(C类)，并参与国家重点研发计划、科技创新2030“新一代人工智能”重大科技项目等多项国家级重点科研项目。担任 IEEE TNSE、ACM MM 等多个国际期刊会议审稿人，获博士研究生国家奖学金、校长特别奖等荣誉。
大小模型端云协同 (Device-Cloud Collaboration between Large and Small Models)
移动端智能体 (On-Device Intelligent Agents)
轻量化持续学习 (Lightweight Continual Learning)
Haibo Liu Chenxin Mao, Zhenzhe Zheng, Fan Wu, Guihai Chen, He Huang. Lethe: Plasticity-aware Active Forgetting for Resource-Efficient On-Device Continual Learning. ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2026, DOI:10.1145/3770855.3817621 (KDD'26, CCF-A类会议).
Haibo Liu, Chen Gong, Zhenzhe Zheng, Fan Wu, Guihai Chen, He Huang. Well Begun is Half Done: Efficient Initialization for Online Continual Learning via Two-Stage Model Merging. ACM International Conference on Multimedia, 2026, DOI:10.1145/3767308.3835269 (MM'26, CCF-A类会议).
Chenxin Mao, Haibo Liu, Zhenzhe Zheng, Fan Wu, Guihai Chen. Smaller But Better: Plasticity-Preserving Continual Learning for Embedded AI. ACM Web Conference, 2026:4952-4961 (WWW'26 CCF-A类会议).
Haibo Liu, Zhenzhe Zheng, Fan Wu, Guihai Chen. From Non-IID to IID: Mobility-aware Hierarchical Federated Learning with Client-Edge Association Control. IEEE Transactions on Mobile Computing, vol. 24, no. 11, pp. 11717-11730, Nov. 2025, DOI: 10.1109/TMC.2025.3585538 (TMC'25 CCF-A类期刊).
Haibo Liu, Da Huo, Zhenzhe Zheng, Fan Wu. Latency-aware Online Continual Learning for Non-Stationary Data Streams.IEEE International Conference on Computer Communications, 2025:1-10, DOI: 10.1109/INFOCOM55648.2025.11044660 (INFOCOM'25 CCF-A类会议).
Haibo Liu, Chen Gong, Zhenzhe Zheng, Shengzhong Liu, Fan Wu. Enabling Real-Time Inference in Online Continual Learning via Device-Cloud Collaboration. ACM Web Conference, 2025：2043-2052, DOI:10.1145/3696410.3714796 (WWW'25 CCF-A类会议).
Haibo Liu, Jianfeng Lu, Xiong Wang, Chen Wang, Riheng Jia, Minglu Li. FedUP: Bridging Fairness and Efficiency in Cross-Silo Federated Learning. IEEE Transactions on Services Computing, vol. 17, no. 6, pp. 3672-3684, Nov.-Dec. 2024, DOI: 10.1109/TSC.2024.3489437 (TSC'24 CCF-A类期刊).
Jianfeng Lu, Haibo Liu, Riheng Jia, Zhao Zhang, Xiong Wang, Jiangtao Wang. Incentivizing Proportional Fairness for Multi-task Allocation in Crowdsensing. IEEE Transactions on Service Computing, vol. 17, no. 3, pp. 990-1000, May-June 2024, DOI: 10.1109/TSC.2023.3325636 (TSC'24 CCF-A类期刊).
Jianfeng Lu, Haibo Liu, Riheng Jia, Jiangtao Wang, Lichao Sun, Shaohua Wan. Towards Personalized Federated Learning Via Group Collaboration in IIoT. IEEE Transactions on Industrial Informatics, vol. 19, no. 8, pp. 8923-8932, Aug. 2023,DOI: 10.1109/TII.2022.3223234 (TII'23 SCI-I区TOP期刊).
Jianfeng Lu, Haibo Liu, Zhao Zhang, Jiangtao Wang, Shaohua Wan. Toward Fairness-aware Time-sensitive Asynchronous Federated Learning for Critical Energy Infrastructure. IEEE Transactions on Industrial Informatics, vol. 18, no. 5, pp. 3462-3472 2022 (TII'22, SCI-I区TOP期刊).
I am constantly looking for well motivated students (both undergrad and graduate) who are interested in on-device agentic AI, intelligent mobile computing, performance analysis and algorithm design, and system implementations. Please email me if you are interested. (2027年有招生名额，欢迎联系！)