教育经历

1.2013-2018，伦敦帝国理工（英国），自动化专业，博士

2.2012/9-2013/10，伦敦帝国理工（英国），控制系统专业，硕士

3.2011/8–2012/6，格拉斯哥大学（英国），电子电气工程专业，学士

4.2008/9–2012/7，天津大学，测控技术与仪器专业，学士

研究方向

1.车辆动力学与控制，多体机械系统建模

2.鲁棒控制理论在机械和电子系统的应用

3.主动可变几何悬架系统的建模和控制，提升乘客舒适性和汽车稳定性

代表性研究成果

(1)Zhu H, Cheng C, Yin H, et al. Automatic multilabel electrocardiogram diagnosis of heart rhythm or conduction abnormalities with deep learning: a cohort study[J]. The Lancet Digital Health, 2020.

(2)C. Cheng, S. Evangelou, C. Arana and D. Dini, "Active variable geometry suspension robust control for improved vehicle ride comfort and road holding", IEEE American Control Conference(ACC), 2015.

(3)C.ChengandS. Evangelou, "Series active variable geometry suspension robust control based onfull-vehicle dynamics", Journal of Dynamic Systems, Measurement, and Control, 2019, 141(5):051002.

(4)Cheng C, Ma G, Zhang Y, et al. A deep learning-based remaining useful life prediction approach for bearings[J]. IEEE/ASME Transactions on Mechatronics, 2020.

(5)Yuan Y, Ma G, Cheng C, et al. A general end-to-end diagnosis framework for manufacturing systems[J]. National Science Review, 2020, 7(2): 418-429.

(6)Ma G, Zhang Y, Cheng C, et al. Remaining useful life prediction of lithium-ion batteries based on false nearest neighbors and a hybrid neural network[J]. Applied Energy, 2019, 253: 113626.

(7)Cheng C, Zhou B, Ma G, et al. Wasserstein distance based deep adversarial transfer learning for intelligent fault diagnosis with unlabeled or insufficient labeled data[J]. Neurocomputing, 2020, 409: 35-45.

联系方式

邮箱：cheng.cheng12@imperial.ac.uk

地址：18luck新利电竞 南一楼中315