上海交通大学自动化系

招生信息

陈宏田，博士生导师
博士后：欢迎随时联系
博士生：欢迎研究方向为复杂系统的故障诊断与控制、分布式智能控制与优化、数据驱动学习与优化、可解释性人工智能技术等相关方向学生报考
硕士生：以学生未来规划为导向，本课题组采取不同的培养措施。对于有读博士意向的学生，注重学术思维和动手实践的培养，为后续的科研之路夯实基础；对于工作意向的同学，依托课题组的项目和实验条件，提升动手实践和综合素养
本科生：长期接收未来准备出国、希望本科阶段参与科研的同学加入课题组进行研究、做毕业设计

教育经历

2015年-2019年，南京航空航天大学，博士学位
2008年-2015年，南京师范大学，学士、硕士学位

工作经历

2023年2月-至今，上海交通大学自动化系，副教授
2019年-2023年，University of Alberta，博士后

科研方向

故障诊断与容错控制
数据驱动技术、可解释性人工智能技术
系统辨识与优化
高速列车
海陆空系统

荣誉与奖励

1) IEEE RCAE杰出青年科学家, 2022年
2) 中国自动化学会优博, 2020年
3) 江苏省优秀博士论文, 2020年
4) 工信部创新奖特等奖, 2019年

学术兼职

1) IEEE Transactions on Instrumentation & Measurement，编委
2) IEEE Transactions on Neural Networks and Learning Systems，客座编委
3) IEEE Transactions on Artificial Intelligence，客座编委
4) Control Engineering Practice，客座编委
5) 5th ICRCAE大会，组织主席
6) IEEE工业电子学会“基于数据的控制与监测”技术委员会，秘书

科研项目

国家自然科学基金：高速列车信息控制系统微小和复合故障的实时诊断理论与预测方法
加拿大自然科学基金探索项目：Robust Process Identification with Dynamic Feature Analysis

代表性论文

[1] Hongtian Chen and Bin Jiang. A review of fault detection and diagnosis for the traction system in high-speed trains. IEEE Transactions on Intelligent Transportation Systems, 2020, 21(2): 450-465.
[2] Hongtian Chen*, Bin Jiang, Steven X. Ding, and Biao Huang. Data-driven fault diagnosis for traction systems in high-speed trains: A survey, challenges, and perspectives. IEEE Transactions on Intelligent Transportation Systems, 2022, 23(3): 1700-1716.
[3] Hongtian Chen, Zhigang Liu, Cesare Alippi, Biao Huang, Derong Liu. Explainable intelligent fault diagnosis for nonlinear dynamic systems: From unsupervised to supervised learning. IEEE Transactions on Neural Networks and Learning Systems, 2022, early access.
[4] Hongtian Chen, Bin Jiang, Wen Chen, and Hui Yi. Data-driven detection and diagnosis of incipient faults in electrical drives of high-speed trains. IEEE Transactions on Industrial Electronics, 2018, 66(6), 4716-4725.
[5] Hongtian Chen, Bin Jiang, Steven X. Ding, Ningyun Lu, and Wen Chen. Probabilityrelevant incipient fault detection and diagnosis methodology with applications to electric drive systems. IEEE Transactions on Control Systems Technology, 2018, 27(6), 2766-2773.
[6] Hongtian Chen, Hui Yi, Bin Jiang, Kai Zhang, and Zhiwen Chen. Data-driven detection of hot spots in photovoltaic energy systems. IEEE Transactions on Systems, Man and Cybernetics: Systems, 2019, 49(8), 1731-1738.
[7] Hongtian Chen, Zheng Chai, Oguzhan Dogru, Bin Jiang, and Biao Huang. Data-driven designs of fault detection systems via neural network-aided learning. IEEE Transactions on Neural Networks and Learning Systems, 2022, 33(10), 5694-5705.
[8] Hongtian Chen, Zhiwen Chen, Zheng Chai, Bin Jiang, and Biao Huang. A single-side neural network-aided canonical correlation analysis with applications to fault diagnosis. IEEE Transactions on Cybernetics, 2022, 52(9), 9454-9466.
[9] Hongtian Chen, Bin Jiang, and Ningyun Lu. A newly robust fault detection and diagnosis method for high-speed trains. IEEE Transactions on Intelligent Transportation Systems, 2018, 20(6), 2198-2208.
[10] Hongtian Chen, Bin Jiang, Wen Chen, and Ziheng Li. Edge computing aided framework of fault detection for traction control systems in high-speed trains. IEEE Transactions on Vehicular Technology, 2019, 69(2): 13091318.

代表性专著

Hongtian Chen, Bin Jiang, Ningyun Lu, Wen Chen. Data-driven Detection and Diagnosis of Faults in Traction Systems of High-speed Trains. Springer Nature, 2020.