研究方向
系统科学角度：复杂系统的机理认知与调控，包括结构推断、预测生成、模型辨识与优化调控、网络安全等。
数据科学/AI角度：因果推断/发现、深度生成/预测模型、动力学辨识/回归/重构、协同控制与优化、大模型训练与推理。
网络科学角度：复杂网络涌现机理（个体间如何互动）、演化规则（预测生成+辨识重构）、调控机制（控制+优化）。
学科交叉角度：系统科学与人工智能的基础理论及其在生命科学、神经科学、智能通信、智能交通、智慧能源等领域应用。
招生需求
1、强烈的科研兴趣（否则以做项目为主）；
2、优秀的编程能力（熟练Python编程）；
3、良好的沟通能力（把自己当作一个学者）；
4、扎实的数学基础（多多益善）；
博士/硕士研究生招生方向/专业来自：计算机、软件、人工智能、数学、系统科学、数据科学、自动化、物理等。
培养方式：以科研创新为核心，以服务国家重大战略为导向，课题组培养模式，根据学生兴趣与基础分配具体研究小组。
培养理念：解决真问题、真解决问题、鼓励学科交叉，基础理论与应用并重，培养新时期学科交叉大环境下的综合型人才。
招生专业：系统科学（硕士）、统计学或数学（硕士）；系统科学（博士）。其他专业报考需联系我在系统选择相应专业。
近五年部分学术论文（*通讯作者）
1. X. Liu, D. Chen*, W. Wei, X. Zhu, W. Yu, Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction, ICLR, 2024, May 7th-11th, Vienna, Austria.
2. X. Liu, D. Chen*, W. Wei, X. Zhu, H. Shi, W. Yu*, System Identification with Fourier Transformation for Long-term Time Series Forecasting, IEEE Transactions on Big Data, 2024, DOI: 10.1109/TBDATA.2024.3407568, in press.
3. X. Liu, Qi. Shao, D. Chen*, Long-term Prediction on Graph Data with Causal Network Construction, IEEE Transactions on Artificial Intelligence, 2024, 5(7): 3445-3455.
4. M. Kang, R. Zhu, D. Chen*, C. Li, W. Gu, X. Qian, W. Yu*, A Cross-modal Generative Adversarial Network for Scenarios Generation of Renewable Energy, IEEE Transactions on Power Systems, 2024, 39(2): 2630-2640.
5. M. Kang, R. Zhu, D. Chen*, X. Liu, W. Yu*, CM-GAN: A Cross-Modal Generative Adversarial Network for Imputing Completely Missing Data in Digital Industry, IEEE Transactions on Neural Network and Learning Systems, 2024, 35(3): 2917-2926.
6. Q. Shao, D. Chen*, W. Yu*, A Unique Framework of Heterogeneous Augmentation Graph Contrastive Learning for Both Node and Graph Classification, IEEE Transactions on Network Science and Engineering, 2024, DOI: 10.1109/TNSE.2024.3454993, in press.
7. M. Wei, W. Yu*, H. Liu, D. Chen*, Byzantine-Resilient Distributed Bandit Online Optimization in Dynamic Environments, IEEE Transactions on Industrial Cyber-Physical Systems, 2024, 2: 154-165.
8. C. Qiu, Y. Li, M. Kang, D. Chen*, W. Yu*, CDSTTN: A Data Imputation Method for Cyber-Physical Systems by Causal Dense Spatial-Temporal Transformer Network, IEEE Journal on Emerging and Selected Topics in Circuits and Systems, 2023, 13(3): 851-860.
9. D. Chen, Q. Shao, Z. Liu, W. Yu*, P. C. L. Chen, Ridesourcing behavior analysis and prediction: A network perspective, IEEE Transactions on Intelligent Transportation Systems, 2022, 23(2): 1274-1283.
10. M. Kang, D. Chen*, N. Meng, G. Yan, W. Yu*, Identifying Unique Causal Network from Nonstationary Time Series, arXiv:2211.10085, 2022.
11. D. Chen, X. Liu, W. Yu, L. Zhu, Q. Tang*, Neural-Network based adaptive self-triggered consensus of nonlinear multi-agent systems with sensor saturation, IEEE Transactions on Network Science and Engineering, 2021, 8 (2): 1531-1541.
12. D. Chen, X. Liu, W. Yu*, Finite-time fuzzy adaptive consensus for heterogeneous nonlinear multi-agent systems, IEEE Transactions on Network Science and Engineering, 2020, 7(4): 3057-3066.
13. D. Chen, Y. Yang, Y. Zhang, W. Yu*, Prediction of COVID-19 Spread by Sliding mSEIR Observer, SCIENCE CHINA Information Sciences, 2020, 63(12): 222203.
14. Q. Tang, D. Chen*, X. He, Integration of enhanced flux linkage observer and I-f starting method for wide speed-range sensorless SPMSM drives, IEEE Transactions on Power Electronics, 2020, 35(8): 8374-8383.
15. D. Chen, W. Li, X. Liu, W. Yu, Y. Sun*, Effects of measurement noise on flocking dynamics of Cucker-Smale systems, IEEE Transactions on Circuits and Systems II: Express Briefs, 2020, 67(10), 2064-2068.
