研究领域

分布式机器学习，去中心化学习，多智能体强化学习，大模型Agent/Multi-Agent System

个人简介

刘博，深圳理工大学助理教授，副研究员，博士生导师。2021年于英国曼彻斯特大学获得电气与电子工程博士学位（PDS全额奖学金），并获得2021年国家优秀自费留学生奖学金（全球650人/年），主持/参与国家、省、市各级别纵向项目5项，在ICML、NeurIPS、CVPR、AAAI、IEEE TAC、TNNLS、 TCYBER、 TMC、TCE等人工智能顶级期刊和会议发表论文30余篇。

学习经历

2017-2021 曼彻斯特大学 博士

2014-2017 武汉理工大学 硕士

2010-2014 武汉理工大学 学士

工作经历

2025-至今，深圳理工大学，教研助理教授、特聘副教授

2021-2025，深圳市人工智能与机器人研究院，历任助理研究员，副研究员

所获荣誉

2021年国家优秀自费留学生奖学金（全球650人/年）

2024年深圳市第四届优秀科技学术论文奖（2篇）

科研项目

[1]国家自然科学基金-青年基金，面向异构多智能体的分布式学习群体策略优化研究，2023-01-01至2025-12-31，30万，主持。
[2]广东省自然科学基金-面上项目，异构交通参与者协同轨迹预测与群体均衡决策研究，2024-01-01至2026-12-31，15万，主持。
[3]深圳市科技创新人才-博士启动计划，基于邻域信息融合的分布式多智能体强化学习交通灯控制研究，2023-04-01至2025-04-01，30万，主持。

代表性论文

[1]L. Yang, J. Sun, C. Cai, X. Liu, Y. Li, B. Peng, J. Li, B. Liu*, “DecFus: Decentralized Layer-wise Fusion with Dynamic Exploration and Exploitation,” International Conference on Machine Learning (ICML), 2026. (CCF-A)
[2]X. Liu, J. Hou, C. Wu, X. Cong, S. Deng, J. Li, L. Deng*, B. Liu*, “Physics-informed Neural Operator for Pansharpening,” Advances in Neural Information Processing Systems (NeurIPS), 2025. (CCF-A)
[3]X Liu, P. Han, X Li, B. Liu*, “SemiDFL: A Semi-Supervised Paradigm for Decentralized Federated Learning,” Proceedings of the AAAI Conference on Artificial Intelligence (AAAI), 2025. (CCF-A)
[4]P. Sun, Y. Liu, Z. Wang and B. Liu*, “Byzantine-robust Decentralized Federated Learning via Dual-domain Clustering and Trust Bootstrapping,” Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024. (CCF-A)
[5]P. Han, B. Liu*, Y. Liu, and L. Guo, “Cell-Less Offloading of Distributed Learning Tasks in Multi-Access Edge Computing,” IEEE Transactions on Mobile Computing (IEEE TMC), vol. 23, no. 12, pp. 14377-14395, 2024. (CCF-A, 深圳市第四届优秀科技学术论文奖)
[6]W. Ye, Y. Luo, B. Liu* (刘博) and J. Huang*, “Efficient and Cost-effective Vehicle Recruitment for HD Map Crowdsourcing,” in IEEE Transactions on Mobile Computing (IEEE TMC), vol. 24, no. 8, pp. 7505–7518, 2025. (CCF-A)
[7]Q. Huang, Y. Li*, B. Liu*, G. Liang, J. Zhao, and C. Courcoubetis, “Pricing Demand-side Flexibility via Mean-field Reverse Stackelberg Game,” IEEE Transactions on Consumer Electronics (IEEE TCE), vol. 71, no. 4, pp. 11133–11145, 2025. (中科院一区Top)
[8]Z. Li, B. Liu and Z. Ding, “Consensus-based cooperative algorithms for training over distributed data sets using stochastic gradients,” IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), vol. 33, no. 10, pp. 5579-5589, 2022. (中科院一区Top)
[9]B. Liu and Z. Ding, “Distributed heuristic adaptive neural networks with variance reduction in switching graphs,” IEEE Transactions on Cybernetics (IEEE TCYB), vol. 51, no. 7, pp. 3836-3844, 2021. (中科院一区Top)
[10]B. Liu, Z. Ding and C. Lv, “Distributed training for multi-layer neural networks by consensus,” IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), vol. 31, pp. 1771-1778, 2020. (中科院一区Top)