个人简介

甘叠，永利3044noc副教授。2017年本科毕业于山东大学数学学院华罗庚班，2022年博士毕业于中国科学院数学与系统科学研究院，2022-2024在中关村国家实验室从事博士后研究工作。在IEEE TAC、Automatica、SICON等学术期刊和会议发表完成论文近30篇。相关成果获获北京数学会首届青年优秀论文奖(1/2)、中国系统科学大会最佳张贴论文奖(1/2)，并被 IEEE Fellow、IFAC Fellow 等知名学者公开评价为研究分布式随机逼近的最弱条件(weakest excitation condition)与最好结果(best ones)。主持国家/省部级项目4 项，授权国家发明专利 3 项。获北京市优秀毕业生(省部级)、博士生国家奖学金等奖项。

一直致力于分布式辨识理论与方法研究，针对已有方法在数据条件、模型结构等方面局限，构造了分布式随机梯度算法、分布式阶估计算法、分布式稀疏辨识算法等一系列原创性方法，突破了从局部量测到全局估计，从开环独立到闭环反馈，从无穷数据到有限数据的技术瓶颈，解决了复杂系统自适应估计、最弱激励条件探索等基本科学问题，并将相关成果应用于目标定位、无线通信等工程领域与司法复杂系统量刑计算等社科领域，构造了更为有效的智能算法。

目前课题组主要围绕“智能学习”与“智能控制”开展研究，从事相关基础理论与实际应用研究，所涉及的具体方向包括：

1. 多智能体协同控制

2. 分布式自适应学习

3. 联邦学习与隐私保护

4. 智能机器人定位导航

5. 合作-竞争并存博弈系统

欢迎品德优秀 (特别是诚实、守信、合作与礼貌等)，有扎实的数理基础和较好的编程能力，做事积极主动，并且对科研工作真正热爱的同学前来报考，一起共同进步！邮箱：gandie@nankai.edu.cn。

科研项目、成果、获奖、专利

科研项目

1. 天津市自然科学基金青年项目（省部级）， 2024/10-2026/09，主持

2. 中国博士后科学基金站中特别资助项目（国家级）， 2023/07-2024/07，主持

3. 中国博士后科学基金第72批面上资助项目（国家级），2022/12-2024/07，主持

4. 复杂系统研究生基金（省部级），2021/01-2022/06，主持

专利

1. 甘叠, 刘志新, 吕金虎. 一种分布式自适应协同跟踪定位方法，2023.8，发明专利，ZL202310581146.9

2. 甘叠, 陈书凝, 吕金虎, 陶冶. 一种分布式压缩感知稀疏时变信道估计方法, 2023.11, 发明专利, ZL202311566816.6

3. 陶冶, 吕金虎, 谭少林, 甘叠. 一种安全鲁棒的室内行人轨迹跟踪方法和系统，2024.2，发明专利，ZL202410038094.5

荣誉奖项

1. 2023年北京数学会首届青年优秀论文奖

2. 2022年北京市优秀毕业生（博士）

3. 2021年第五届系统科学大会最佳张贴论文奖

4. 2020年博士生国家奖学金
   

撰写论文、专著、教材等

• 期刊论文（*代表通讯作者）

1. D. Gan, S. Xie, Z. Liu, J. Lv, Stability of FFLS-based diffusion adaptive filter under cooperative excitation condition, IEEE Transactions on Automatic Control, 69(11):7479-7492, 2024.

2. D. Gan, Z. Liu,  Distributed sparse identification for stochastic dynamic systems under cooperative non-persistent excitation condition, Automatica, 151:110958, 2023.

3. D. Gan, R. Yan, S. Chen, Z. Liu, Distributed extended SG algorithm for joint identification of system parameters and noise model parameters, 63(1): 650-675, SIAM Journal on Control and Optimization, 2025. 

4. D. Gan, Z. Liu, Distributed order estimation of ARX model under cooperative excitation condition, SIAM Journal on Control and Optimization, 60(3): 1519-1545, 2022. 

5. D. Gan, Z. Liu, Convergence of the distributed SG algorithm under cooperative excitation condition, IEEE Transactions on Neural Networks and Learning System, 35(5):7087-7101, 2024. 

6. D. Gan, S. Xie, Z. Liu, Stability of the distributed Kalman filter using general random coefficients, Science China Information Sciences, 64: 172204, 2021. 

7. D. Gan, Z. Liu, Performance analysis of the compressed distributed least squares algorithm, Systems & Control Letters, 164: 105228, 2022. 

8. S. Xie, S. Zhang, Z. Wang, D. Gan*, Compressed least squares algorithm of continuous-time linear stochastic regression model using sampling data, Journal of Systems Science and Complexity, 37(4):1488-1506, 2024.  

9. S. Xie, D. Gan*, Z. Liu, Stability analysis of distributed Kalman filtering algorithm for stochastic regression model, Accepted by Control Theory and Technology, December, 2024.

10. S. Xie, D. Gan*, Z. Liu, Two-layer diffusion adaptive filters over directed Markovian switching networks, IEEE Control Systems Letters(with IEEE ACC 2024), 7: 3501-3506, 2023. 

11. R. Li, D. Gan, S. Xie, H. Gu, J. Lv, Analysis of the compressed distributed Kalman filter over Markovian switching topology,  IEEE Transactions on Cybernetics, 55(3): 1372-1384, 2025.

12. R. Li, D. Gan, S. Xie, J. Lv, Stability and performance analysis of the compressed Kalman filter algorithm for sparse stochastic systems, Science China Technological Sciences, 67(2): 380-394, 2024.

13. R. Li, D. Gan, H. Gu, J. Lv, Distributed state estimation for sparse stochastic systems based on compressed sensing, IEEE Transactions on Circuits and Systems II: Express Briefs, 71(8):3840-3844, 2024.

14. X. Zhu, D. Gan, Z. Liu, Performance analysis of least squares of continuous-time model based on sampling data, IEEE Control Systems Letters (with IEEE CDC 2022), 6: 3086-3091, 2022.

15. X. Zhu, D. Gan, Z. Liu, Distributed least squares algorithm of continuous-time stochastic regression model based on sampled data, Journal of Systems Science and Complexity, 37(2):609-628, 2024. 

16. R. Li, G. Chen, D. Gan, H. Gu, J. Lv, Stackelberg and Nash equilibrium computation in non-convex leader-follower network aggregative games, IEEE Transactions on Circuits and Systems I: Regular Papers, 71(2):898-909, 2024. 

17. 王芳，甘叠，刘念，认罪认罚量刑从宽实效研究——基于故意伤害罪轻罪的数据解读，山东大学学报(哲学社会科学版)，2022年第3期，65-77.（中文核心）

18. S. Xie, R. Li, D. Gan*, Distributed extended least squares algorithm over directed graphs, Automatica, 2025. (under review)

19. S. Chen, D. Gan, S. Xie, J. Lv, Distributed sparse adaptive estimation over Markov switching topologies, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024.  (under 2nd review) 
    

20. S. Chen#, D. Gan#, S. Xie, J. Lv, Privacy-preserving distributed adaptive estimation for non-stationary regression data, Systems & Control Letters, 2025.  (under review)

21. S. Xie, Y. Xu, R. Lin, D. Gan, S. Luo, Collaborative spectum sensing based on distributed adaptive filtering, IEEE Open Journal of the Communications Society, 2025.  (under review) 

• 会议论文（*代表通讯作者）

1. D. Gan, Z. Liu, On the stability of Kalman filter with random coefficients, IFAC-PapersOnLine, 53(2):2397-2402, 2020. 

2. D. Gan, Z. Liu, Strong consistency of the distributed stochastic gradient algorithm, Proceedings of IEEE 58th Conference on Decision and Control, Nice, France, pp. 5082-5087, 2019.

3. S. Chen, D. Gan*, K. Liu, J. Lv, Stability of compressed recursive least squares with forgetting factor algorithm, IFAC-PapersOnLine, 56(2):10240-10245, 2023.

4. S. Chen, D. Gan*, S. Xie, J. Lv, Tracking bound of compressed distributed recursive least squares with forgetting factor,  Proceedings of the 14th Asian Control Conference, China, Dalian, pp. 2434-2439, 2024.

5. D. Gan, R. Li, Logarithmic regret bound for distributed adaptive sparse estimation without excitation condition, Proceedings of the 15th International Workshop on Adaptive and Learning Control Systems, 2025. (under review)

6. D. Gan, Y. Xu, S. Xie, Distributed adaptive identification for stochastic large models with infinite unknown parameters, Proceedings of the 44th Chinese Control Conference, 2025. (under review)

讲授课程

社会兼职

《控制理论与应用》中、英文刊青年编委

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