Faculty
	Prof. Dong SHEN E-mail: dshen [at] ieee.org Tel: 010-82507078 Office: Rm 207, Mathematics Building Web: @DAI @RUC @ResearchGate
	Assoc. Prof. Hao JIANG Email: jiangh [at] ruc.edu.cn Office: Rm 223, Mathematics Building Web: @DAI @RUC @ResearchGate
	Assoc. Prof. Qijiang SONG Emai: sqj [at] ruc.edu.cn Tel: 010-82500693 Office: Rm 337, Information Building Web: @DAI @RUC @ResearchGate
	Assit. Prof. Xiuqiong CHEN Email: cxq0828 [at] ruc.edu.cn Office: Room 327, Information Building Web: @DAI @RUC
Ph. D Candidate
	HUANG Shunhao | 2020 Topic: GPR-based Learning Control M.E., Beijing University of Chemical Technology Publications: [1] Hao Jiang, Dong Shen, Shunhao Huang, Xinghuo Yu. Accelerated Learning Control for Point-to-Point Tracking Systems. IEEE Transactions on Neural Networks and Learning Systems, accepted. [2] Shunhao Huang, Dong Shen, JinRong Wang. Point-to-Point Learning Tracking Control via Fading Communication Using Reference Update Strategy. IEEE Transactions on Cybernetics, accepted.
	ZHAO Xingying | 2020 Topic: Federated Learning and Its Applications M.E., Beihang University Publications: [1] Xing-Ying Zhao, Hao Jiang, Dong Shen. EOGFACE: Deep Face Recognition Via Extensional Logits.  2022 IEEE International Conference on Image Processing. 2022 IEEE International Conference on Image Processing, Bordeaux, France, 16-19 October, 2022, pp. 311-315. [2] Xingying Zhao, Dong Shen. FedLoss: Logits Replacement of Softmax for Federated Learning Face Recognition. Submitted. [3] Xingying Zhao, Dong Shen. Federated Learning with Adaptive Sample Weights Based on Self-paced Learning. Submitted.
	QIAN Jiaxi | 2021 Topic: Optimization-Based ILC B.S., Jilin University Publications: [1] Dong Shen, Jiaxi Qian. Recent Advances in Iterative Learning Control with Fading Channel. 2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS'21), Suzhou, China, 14-16 May, 2021. [2] Jiaxi Qian, Dong Shen. A Novel Iterative Learning Control Scheme Based on Broyden-class Optimization Method. International Journal of Robust and Nonlinear Control, accepted for publication.
	HUO Niu | 2021 Topic: Quantized Iterative Learning Control M.E., Beijing University of Chemical Technology Awards: Selected, 2022 Funding Program for Cultivating top-notch innovative Talents of Renmin University of China Publications: [1] Niu Huo, Hao Jiang, Dong Shen, Jinrong Wang. Finite-Level Uniformly Quantized Learning Control with Random Data Dropouts. International Journal of Robust and Nonlinear Control, 2022. [2] Dong Shen, Niu Huo, Samer S. Saab. A Probabilistically Quantized Learning Control Framework for Networked Linear Systems, IEEE Transactions on Neural Networks and Learning Systems, 2021.
	HE Xun | 2020(M) 2022(D) Topic: Learning Control for Complex Networks B.S., Qufu Normal University Awards: Selected, Graduate Scientific Research Fund Project of Renmin University of China Publications: [1] Xun He, Dong Shen. Distributed Iterative Learning Temperature Control for Large-Scale Buildings. International Journal of Robust and Nonlinear Control, accepted for publication. [2] Hao Jiang, Xun He, Qijiang Song, Dong Shen. Decentralized Learning Control for Large-Scale Systems With Gain Adaptation Mechanism. Information Sciences, vol. 623, pp. 539-558, 2023. [3] Xun He, Hao Jiang, Dong Shen. Iterative Learning Control for Multi-Agent Systems Over Unknown Fading Networks. The IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS'22), Emeishan, China, 3-5 August, 2022, pp. 976-981.
	LIU Taojun | 2022 Topic: Learning Control with Dynamic Quantization Mechanisms B.S., Dalian University of Technology
	CHENG Xiang | 2020(M) 2023(D) Topic: Variable Gain Design in ILC B.S., University of Science and Technology Beijing Awards: 2022 China National Scholarship Publications: [1] Xiang Cheng, Hao Jiang, Dong Shen, Xinghuo Yu. A Novel Adaptive Gain Strategy for Stochastic Learning Control. IEEE Transactions on Cybernetics, 2022, accepted. [2] Xiang Cheng, Hao Jiang, Dong Shen. A Novel Accelerated Multi-Stage Learning Control Mechanism via Virtual Performance Reduction. IEEE Transactions on Neural Networks and Learning Systems, 2022, accepted
	ZHANG Zeyi | 2020(M) 2023(D) Topic: New Design Techniques in ILC B.S., Qingdao University Awards: 2022 China National Scholarship Publications: [1] Zeyi Zhang, Dong Shen. Randomized Kaczmarz Algorithm with Averaging and Block Projection. Submitted. [2] Zeyi Zhang, Hao Jiang, Dong Shen, Samer S. Saab. Learning Control Algorithms for Inconsistent Tracking Problems.IEEE/CAA Journal of Automatica Sinica, accepted. [3] Dong Shen, Xinghuo Yu, Zeyi Zhang. Multi-Objective Learning Tracking Scheme Over Multiple Fading Channels. Submitted. [4] Zeyi Zhang, Hao Jiang, Dong Shen. Extended Iterative Learning Control for Inconsistent Tracking Problems with Random Dropouts. The IEEE 11th Data Driven Control and Learning Systems Conference (DDCLS'22), Emeishan, China, 3-5 August, 2022, pp. 935-940. [5] Zeyi Zhang, Hao Jiang, Kun Zeng, Dong Shen. Collaborative Learning Tracking for Networked Systems With Fading Communication. The IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS'23).
Master Candidate
	LI Zihan | 2021 Topic: Fractional-power Learning Control Rules B.S., Hunan University Publications: [1] Zihan Li, Dong Shen. Finite and Fixed-Time Learning Control for Continuous-Time Nonlinear Systems. Submitted. [2] Zihan Li, Dong Shen. Filter-Free Parameter Estimation Method for Continuous-Time Systems. IEEE Transactions on Automation Science and Engineering, accepted for publication. [3] Zihan Li, Dong Shen, Xinghuo Yu. Enhancing Iterative Learning Control With Fractional Power Update Law. IEEE/CAA Journal of Automatica Sinica, vol. 10, no. 5, pp. 1137-1149, 2023.
	LUO Qiaoqiao | 2021 Topic: Learning Control under Network Attacks B.S., Shandong University
	WANG Yingchao | 2021 Topic: Event-triggered Learning Control B.S., Qufu Normal University
	GAO Shuai | 2021 Topic: Learning Control for High-Speed Trains B.S., Shaanxi Normal University Publications: [1] Shuai Gao, Qijiang Song, Dong Shen.Decentralized Learning Control for High-Speed Trains with Unknown Time-Varying Speed Delays. Submitted. [2] Shuai Gao, Qijiang Song, Dong Shen. Distributed Learning Control for High-Speed Trains With Operation Safety Constraints. IEEE Transactions on Cybernetics. Accepted for publication. [3] Shuai Gao, Dong Shen. Iterative Learning Control for High-Speed Trains with Nonuniform Operation Lengths. The 13th Asian Control Conference, Jeju, Korea, 3-7 May, 2022, pp. 137-142. [4] Shuai Gao, Qijiang Song, Hao Jiang, Dong Shen. History Makes Future: Iterative Learning Control for High-Speed Trains. IEEE Intelligent Transportation Systems Magazine. Accepted for publication.
	ZHOU Yujian | 2021 Topic: Machine Learning and Its Applications B.S., Tsinghua University
	ZHAN Senwen | 2021 Topic: Machine learning and Its Applications B.S., Huazhong University of Science and Technology
	HUANG yixiang｜2021 Topic: Machine Learning in Bioinformatics B.S., Shandong University
	ZHANG Zhenfa | 2022 Topic: Multi-objective Learning Control B.S., Shandong University
	HUANG Dunsheng | 2022 Topic: Wavelet-based Learning Approximation B.S., Beijing Jiaotong University
	DU Bowen | 2022 Topic: Learning Control for HSTs B.S., Unversity
	WANG Chi | 2022 Topic: Bioinformatics B.S., Unversity
	ZHOU Zimo | 2022 Topic: Bioinformatics B.S., Unversity
	CHANG Junji | 2022 Topic: Learning Control Under Noise Correlation B.S., University
Undergraduates
	Recruiting
Visiting Students
	Recruiting

	AI Yutong | M.S. Graduated 2023.06 Topic:Graph Neural Networks and its applications B.S.,Renmin University of China
	WANG Mengjie | M.S. Graduated 2023.06 Topic: Machine learning on Bioinfomatics B.S.,Jilin University
	ZENG Kun | M.E. Graduated 2023.06 Topic: Iterative Learning Containment Control for Multi-Agent Systems B.E., Beihang University Book Chapter: [1] Kun Zeng. Iterative Learning Control for FinTech. Proceedings of the First International Forum on Financial Mathematics and Financial Technology, Chapter 15. Springer, 2021.
	DOU Yiyao | M.S. Graduated 2022.06
	FENG Yifan | M.S. Graduated 2022.06
	QU Ganggui | M.E. Graduated 2021.06 Thesis: Iterative Learning Control Over Fading Channel Following Position: Engineer in a company Awards: 2019 China National Scholarship Journal Papers: [1] Ganggui Qu, Dong Shen. Stochastic Iterative Learning Control With Faded Signals. IEEE/CAA Journal of Automatica Sinica, vol. 6, no. 5, pp. 1196-1208, 2019. [2] Dong Shen, Ganggui Qu, Qijiang Song. Learning Control for Networked Stochastic Systems With Fading Communication. IEEE Transactions on Systems, Man, and Cybernetics-Systems, accepted for publication. [3] Dong Shen, Ganggui Qu. Learning Tracking Systems Over Fading Channels with Multiplicative and Additive Randomness. IEEE Transactions on Neural Networks and Learning Systems, vol. 31, no. 4, pp. 1196-1210, 2020. [4] Dong Shen, Ganggui Qu, Xinghuo Yu. Averaging Techniques for Balancing Learning and Tracking Abilities Over Fading Channels. IEEE Transactions on Automatic Control, accepted for publication. [5] Ganggui Qu, Dong Shen, Qijiang Song, Xinghuo Yu. Point-to-Point Learning and Tracking for Networked Stochastic Systems With Fading Communications. Submitted for publication. [6] Ganggui Qu, Dong Shen, Xinghuo Yu. Batch-Based Learning Consensus of Multi-Agent Systems With Faded Neighborhood Information. IEEE Transactions on Neural Networks and Learning Systems. accepted.
	HUO Niu | M.E. Graduated 2021.06 Thesis: Research on Quantized Iterative Learning Control Following Position: PhD candidate, Renmin University of China Awards: 2019 China National Scholarship Journal Papers: [1] Niu Huo, Dong Shen. Finite-level Quantized Iterative Learning Control with Encoding and Decoding Mechanism with Random Data Dropouts. IEEE Transactions on Automation Science and Engineering, vol. 17, no. 3, pp. 1343-1360, 2020. [2] Niu Huo, Dong Shen. Improving Boundary Level Calculation in Quantized Iterative Learning Control with Encoding and Decoding Mechanism. IEEE Access, vol. 7, no. 1, pp. 66623-66632, 2019. [3] Niu Huo, Dong Shen, Jinrong Wang. Finite-Level Uniformly Quantized Learning Control with Random Data Dropouts. Submitted for publication. [4] Dong Shen, Niu Huo, Samer S. Saab. A Probabilistically Quantized Learning Control Framework for Networked Linear Systems, IEEE Transactions on Neural Networks and Learning Systems.
	LIU Yanze | B.E. Graduated 2021.06 Bachelor Thesis: Iterative Learning Control in Network Environments Journal Papers: [1] Yanze Liu, Dong Shen. An Efficient Algorithm for Collaborative Learning Model Predictive Control of Nonlinear System. ISA Transactions, accepted for publication.
	LIU Chen | M.E. Graduated 2020.06 Co-supervised by Shuming Tang Thesis: Consensus Tracking Iterative Learning Control for Multi-Agent Systems Following Position: PhD candidate, Xi'an Jiaotong University Awards: 2019 China National Scholarship Journal Papers: [1] Chen Liu, Dong Shen, JinRong Wang. Iterative Learning Control of Multi-Agent Systems under Communication Noises and Measurement Range Limitations. International Journal of Systems Science, vol. 50, no. 7, pp. 1465-1482, 2019. [2] Chen Liu, Dong Shen, JinRong Wang. A Two-Dimensional Approach to Iterative Learning Control with Randomly Varying Trial Lengths. Journal of Systems Science and Complexity, vol. 33, no. 3, pp. 685-705, 2020. [3] Chen Liu, Dong Shen, JinRong Wang. Adaptive learning control for general nonlinear systems with nonuniform trial lengths, initial state deviation, and unknown control direction. International Journal of Robust and Nonlinear Control, vol. 29, no. 17, pp. 6227-6243, 2019. [4] Dong Shen, Chen Liu, Lanjing Wang, Xinghuo Yu. Iterative Learning Tracking for Multi-Sensor Systems: A Weighted Optimization Approach. IEEE Transactions on Cybernetics, accepted for publication. [5] Tianbo Zhang, Dong Shen, Chen Liu, Hongze Xu. A Novel Iterative Learning Control Approach Based on Steady-state Kalman Filtering. IEEE Access, vol. 7, no. 1, pp. 99371-99380, 2019.
	ZENG Chun | M.E. Graduated 2019.06 Thesis: Iterative Learning Control with Iteration-Varying Lengths Based on CEF Following Position: China Electronics Technology Group Corporation (Institute 32) Awards: [1] 2018 China National Scholarship [2] 2019 Excellent Master Thesis of BUCT Journal Papers: [1] Chun Zeng, Dong Shen, JinRong Wang. Adaptive Learning Tracking for Uncertain Systems with Partial Structure Information and Varying Trial Lengths. Journal of the Franklin Institute, vol. 355, no. 15, pp. 7027-7055, 2018. [2] Chun Zeng, Dong Shen, JinRong Wang. Adaptive Learning Tracking for Robot Manipulators with Varying Trial Lengths. Journal of the Franklin Institute, vol. 356, no. 12, pp. 5993-6014, 2019.
	ZHANG Chao | M.E. Graduated 2018.12 ahead of schedule Thesis: Quantized Iterative Learning Control Based on Encoding and Decoding Mechanism Following Position: CheetahMobile Awards [1] 2018 IEEE 7th DDCLS Best Paper Award Finalist [2] 2017 China National Scholarship [3] 2016 Top Scholarship of BUCT Journal Papers: [1] Dong Shen, Chao Zhang, Yun Xu. Two Compensation Schemes of Iterative Learning Control for Networked Control Systems with Random Data Dropouts. Information Sciences, vol. 381, pp. 352-370, 2017. [2] Dong Shen, Chao Zhang. Learning Control for Discrete-Time Nonlinear Systems With Sensor Saturation and Measurement Noise. International Journal of Systems Sciences, vol. 48, no. 13, pp. 2764-2778, 2017. [3] Dong Shen, Chao Zhang, Yun Xu. Intermittent and Successive ILC for Stochastic Nonlinear Systems with Random Data Dropouts. Asian Journal of Control, vol. 20, no. 3, pp. 1102-1114, 2018. [4] Dong Shen, Chao Zhang, Jian-Xin Xu. Distributed Neural Networks Based Learning Consensus Control for Heterogeneous Nonlinear Multi-Agent Systems. International Journal of Robust and Nonlinear Control, vol. 29, no. 13, pp. 4328-4347, 2019. [5] Chao Zhang, Dong Shen. Zero-Error Convergence of Iterative Learning Control Based on Uniform Quantization with Encoding and Decoding Mechanism. IET Control Theory & Application, vol. 12, no. 14, pp. 1907-1915, 2018. [6] Chao Zhang, Dong Shen. Zero-Error Learning Tracking Based on Quantized Data via Encoding-Decoding Mechanism at Both Measurement and Actuator Sides. IEEE Transactions on Cybernetics.
	WANG Lanjing | M.E. Graduated 2018.06 Thesis: Iterative Learning Control for Continuous-time Nonlinear Systems with Iteration Varying Lengths Followin position: Sichuan Agricultural University Awards: [1] 2018 Excellent Master Thesis of BUCT Journal Papers: [1] Lanjing Wang, Xuefang Li, Dong Shen. Sampled-data-based Iterative Learning Control for Continuous-time Nonlinear Systems with Iteration-Varying Lengths. International Journal of Robust and Nonlinear Control, vol. 28, no. 8, pp. 3073-3091, 2018. [2] Dong Shen, Chen Liu, Lanjing Wang, Xinghuo Yu. Iterative Learning Tracking for Multi-Sensor Systems: A Weighted Optimization Approach. IEEE Transactions on Cybernetics, accepted for publication.
	ZHANG Fanshou | M.E. Graduated 2018.06 Thesis: Design and Analysis the Algorithms of Smart Car in Environmental Perception and Interaction Co-supervised with Prof. Shuming Tang from Institute of Automation, CAS Following position: Umetrip
	XU Yun | M.E. Graduated 2017.06 Thesis: Iterative Learning Control under Active Incomplete Data Following position: State Administration of Taxation, PRC Awards: [1] 2017 Excellent Master Thesis of BUCT [2] 2016 China National Scholarship [3] 2015 Top Scholarship of BUCT [4] 2014 Top Scholarship of BUCT Journal Papers: [1] Dong Shen, Yanqiong Jin, Yun Xu. Learning Control for Linear Systems under General Data Dropouts at Both Measurement and Actuator Sides: A Markov Chain Approach. Journal of the Franklin Institute, vol. 354, no. 13, pp. 5091-5109, 2017. [2] Yun Xu, Dong Shen, Xuhui Bu. Zero-Error Convergence of Iterative Learning Control Using Quantized Information. IMA Journal of Mathematical Control and Information, vol. 34, no. 3, pp. 1061-1077, 2017. [3] Yun Xu, Dong Shen, Xiao-Dong Zhang. Stochastic Point-to-Point Iterative Learning Control Based on Stochastic Approximation. Asian Journal of Control, vol. 19, no. 5, pp. 1748-1755, 2017. [4] Dong Shen, Chao Zhang, Yun Xu. Intermittent and Successive ILC for Stochastic Nonlinear Systems with Random Data Dropouts. Asian Journal of Control, vol. 20, no. 3, pp. 1102-1114, 2018. [5] Yun Xu, Dong Shen, Youqing Wang. On Interval Tracking Performance Evaluation and Practical Varying Sampling ILC. International Journal of Systems Science, vol. 48, no. 8, pp. 1624-1634, 2017. [6] Dong Shen, Chao Zhang, Yun Xu. Two Compensation Schemes of Iterative Learning Control for Networked Control Systems with Random Data Dropouts. Information Sciences, vol. 381, pp. 352-370, 2017. [7] Dong Shen, Yun Xu. Iterative Learning Control for Discrete-time Stochastic Systems with Quantized Information. IEEE/CAA Journal of Automatica Sinica, vol. 3, no. 1, pp. 59-67, 2016.
	JIN Yanqiong | B.Eng. Graduated 2017.06 Bachelor Thesis: Iterative Learning Control with Data Dropouts at Both Sides Following position: M.E. Candidate, Beihang University Journal Papers: [1] Yanqiong Jin, Dong Shen. Iterative Learning Control for Nonlinear Systems with Data Dropouts at Both Measurement and Actuator Sides. Asian Journal of Control, vol. 20, no. 4, pp. 1624-1636, 2018. [2] Dong Shen, Yanqiong Jin, Yun Xu. Learning Control for Linear Systems under General Data Dropouts at Both Measurement and Actuator Sides: A Markov Chain Approach. Journal of the Franklin Institute, vol. 354, no. 13, pp. 5091-5109, 2017.
	HAN Jian | M.E. Graduated 2016.06 Thesis: Neural Networks Based Point-to-Point Iterative Learning Control Following position: Ph.D Candidate, University of Amsterdam, The Netherlands Journal Papers: [1] Jian Han, Dong Shen, Chiang-Ju Chien. Terminal Iterative Learning Control for Discrete-Time Nonlinear System Based on Neural Networks. Journal of the Franklin Institute, vol. 355, no. 8, pp. 3641-3658, 2018. [2] Dong Shen, Jian Han, Youqing Wang. Stochastic Point-to-Point Iterative Learning Tracking With Unknown System Matrices. IEEE Transactions on Automation Science and Engineering, vol. 14, no. 1, pp. 376-382, 2017. [3] Dong Shen, Jian Han, Youqing Wang. Convergence Analysis of ILC Input Sequence for Underdetermined Linear Systems. SCIENCE CHINA Information Sciences, vol. 60, ID: 099201, 2017.
	ZHANG Wei | M.E. Graduated 2016.06 Thesis: Iterative Learning Control for Discrete-time Systems with Randomly Iteration-Varying Lengths Following position: State Grid Corporation of China Journal Papers: [1] Dong Shen, Wei Zhang, Jian-Xin Xu. Iterative Learning Control for Discrete Nonlinear Systems with Randomly Iteration Varying Lengths. Systems & Control Letters, vol. 96, pp. 81-87, 2016. [2] Dong Shen, Wei Zhang, Youqing Wang, Chiang-Ju Chien. On Almost Sure and Mean Square Convergence of P-type ILC Under Randomly Varying Iteration Lengths. Automatica, vol. 63, no. 1, pp. 359-365, 2016.