邵海滨

职称:助理研究员

邮箱:shore@sjtu.edu.cn

地址:电院群楼2-309

个人主页:https://shaohaibin.github.io

研究方向

群体智能机理及其应用、多自主体系统、分布式学习与优化、城市交通系统

科研成果

1. Lulu PanHaibin Shao*, Yuanlong Li, Dewei Li and Yugeng Xi. Event-triggered Consensus of Matrix-weighted Networks Subject to Actuator SaturationIEEE Transactions on Network Science and Engineering, 2022. (https://doi.org/10.1109/TNSE.2022.3212773)

2. Linli Zhang, Dewei Li, Shuai Jia, Haibin Shao. Brain-Inspired Experience Reinforcement Model for Bin Packing in Varying EnvironmentsIEEE Transactions on Neural Networks and Learning Systems, 2022, 33(5):2168-2180.

3. Chongzhi Wang, Lulu Pan, Haibin Shao*, Dewei Li*, Yugeng Xi. Characterizing bipartite consensus on signed matrix-weighted networks via balancing set. Automatica, 2022. (https://doi.org/10.1016/j.automatica.2022.110237)

4. Lulu Pan, Haibin Shao*, Mehran Mesbahi, Dewei Li, Yugeng Xi. Cluster consensus on matrix-weighted switching networksAutomatica, 2022. (https://doi.org/10.1016/j.automatica.2022.110308)

5. Xiaoxing Ren, Dewei Li, Yugeng Xi, and Haibin ShaoAn accelerated distributed gradient method with local memoryAutomatica, 2022. (https://doi.org/10.1016/j.automatica.2022.110260)

6. Xiaoxing Ren, Dewei Li, Yugeng Xi, and Haibin Shao. Distributed global optimization for a class of nonconvex optimization with coupled constraints. IEEE Transactions on Automatic Control, 2021. (https://doi.org/10.1109/TAC.2021.3115430)

7. Lulu Pan, Haibin Shao*, Mehran Mesbahi, Yugeng Xi and Dewei Li. Consensus on matrix-weighted switching networks. IEEE Transactions on Automatic Control, 2021, 66(12):5990-5996. 
8. Lulu Pan, Haibin Shao*, Mehran Mesbahi, Yugeng Xi and Dewei Li. On the controllability of matrix-weighted networks. IEEE System Control Letter, 2020, 3(4):572-577.
9. Haibin Shao, Lulu Pan, Mehran Mesbahi, Yugeng Xi and Dewei Li. Relative tempo of distributed averaging on networks. Automatica, 2019, 105:159-166.

10. Haibin Shao, Merhan Mesbahi, Dewei Li, and Yugeng Xi. Inferring centrality from network snapshots. Scientific Reports, 2017, 7(1):1-13.

研究项目

1. 上海市自然科学基金(探索类项目),基于类脑学习机理的决策网络及算法研究,2019-06至2022-06, 主持
2. 国家重点研发计划项目,工业机器人中间件关键技术及应用平台研发,2019-01至2021-12,子课题负责人
3. 国家自然科学基金(重点项目),网络化系统分布式实时优化决策理论及应用,2019-01至2023-12,参与
4. 中国博士后科学基金(面上项目),多智能体系统协同的相对节奏及其应用,2018-05至2019-05,主持

教授课程

2022年秋季学期,《数字信号处理技术及应用》,本科生课程

2021年秋季学期,《数字信号处理技术及应用》,本科生课程

2020年秋季学期,《数字信号处理技术及应用》,本科生课程

招生信息

如果您对我的研究方向感兴趣,欢迎联系讨论与咨询!(邮箱:shore [at] sjtu [dot] edu [dot] cn
1. 博士后:招收多自主体系统和分布式学习与优化方向博士后2人.
2. 博士生、硕士生:招收2023年博士生和硕士生.
3. 本科生:欢迎对研究方向感兴趣的同学加入课题组进行科研、竞赛等活动.
返回上一级