学习经历 2012.11 英国爱丁堡大学 基础设施与环境 博士 2007.07 中国科学技术大学 机械电子工程 硕士 2004.07 合肥工业大学 交通工程 学士 工作经历 2018.05-至今 中国科学技术大学精密机械与精密仪器系 特任研究员 2013.11-2018.03 英国拉夫堡大学 航天与汽车工程系 助理研究员 2012.01-2013.10 英国朴次茅斯大学 土木工程与测量系 助理研究员

主要研究包括系统动态检测和数据处理技术、人工智能方法如深度学习、迁移学习等在新能源电池系统、智能制造设备中的应用。此外，还包括采用无损检测方法，对新能源电池在复杂运行条件下的性能衰减机理进行监测和分析

国际工程师协会（International Association of Engineers）会员 国际预测与健康管理组织（Prognostics and Health Management Society）会员 中国振动工程协会故障诊断专业委员会理事

1、Mao, L., Jackson, L., Huang, W., Li, Z., Ben, D. (2020). Polymer electrolyte membrane fuel cell fault diagnosis and sensor abnormality identification using sensor selection method, Journal of Power Sources, 447, 227394. 2、Huang, W., Li, N., Selesnick, I., Shi, J., Wang, J., Mao, L., Jiang, X., Zhu, Z. (2020). Non-convex group sparsity signal decomposition via convex optimization for bearing fault diagnosis. IEEE Transactions on Instrumentation and Measurement, Early Access. 3、Abuker, Y. Y. A., Liu, Z., Mao, L. (2019). Fault classification of polymer electrolyte membrane fuel cell system based on empirical mode decomposition. 2nd World Congress on Condition Monitoring, WCCM 2019, December 2-5, Singapore. 3、Liu, Z., Abuker, Y. Y. A., Mao, L. (2019). A novel method of PEM fuel cell fault diagnosis based on signal-to-image conversion. 2nd World Congress on Condition Monitoring, WCCM 2019, December 2-5, Singapore. 4、Pan, W. T., Abuker, Y. Y. A., Mao, L. (2019). Investigation of feature effectiveness in fault diagnosis of PEM fuel cell system. The 10th IEEE Prognostics and System Health Management Conference. PHM-2019, October 25-27, Qingdao, China. 5、Mao, L., Jackson, L. (2018). Effect of sensor set size on polymer electrolyte membrane fuel cell fault diagnosis. Sensors, 18, 2777. 6、Mao, L., Jackson, L., Davies, B. (2018). Effectiveness of a novel sensor selection algorithm in PEM fuel cell on-line diagnosis. IEEE Transactions on Industrial Electronics. 65, 7301-7310. 7、Mao, L.,Jackson, L., Davies, B. (2018). Investigation of PEMFC fault diagnosis with consideration of sensor reliability. International Journal of Hydrogen Energy. 43, 16941-16948. 8、Mao, L., Goodall, P., Jackson, L., West, A. (2018). Enhanced condition monitoring of the machining process using wavelet packet transform, European Safety and Reliability Conference 2018, 17-21 June, 2018, Trondheim, Norway. 9、Vasilyev, A., Mao, L., Jackson, L., Andrews, J. (2018). The use of bond graph modelling in polymer electrolyte membrane fuel cell fault diagnosis, European Safety and Reliability Conference 2018, 17-21 June, 2018, Trondheim, Norway 10、Lisa Jackson, Melanie-Jane Stoneman, Heather Callaghan, Hanjing Zhang, Cristina Latsou, Sarah Dunnett, Lei Mao.(2018). Influencing Operational Policing Strategy by Predictive Service Analytics. 51st Hawaii International Conference on System Sciences, 03-06 January, 2018, Waikoloa Village, HI, United States. 11、Eleni Tsalapati, Thomas W. Jackson, William Johnson, Lisa Jackson, Andrey Vasilyev, Andrew West, Lei Mao, Ben Davies (2018). The Role of Sematic Technologies in Diagnostic and Decision Support for Service Systems. 51st Hawaii International Conference on System Sciences, 03-06 January, 2018, Waikoloa Village, HI, United States. 12、Mao, L., Lu, Y. (2017). Experimental study of sensitivity-aided application of artificial boundary condition frequencies for damage identification. Engineering Structures, 134, 253-261. 13、Mao, L., Barnett, S.J. (2017). Investigation of toughness of ultra high performance fibre reinforced concrete (UHPFRC) beam under impact loading. International Journal of Impact Engineering, 99, 26-38. 14、Mao, L. *,Jackson, L., Dunnett, S.J. (2017). Fault diagnosis of practical polymer electrolyte membrane (PEM) fuel cell system with data-driven approaches. Fuel Cells, 17, 247-258. 15、Mao, L., Jackson, L. (2016). Selection of optimal sensors for predicting performance polymer electrolyte membrane fuel cell. Journal of Power Sources, 328, 151-160. 16、Mao, L., Jackson, L. (2016). Comparative study on prediction of fuel cell performance using machine learning approaches. Lecture Notes in Engineering and Computer Science. 1, 52-57. 17、Mao, L., Lu, Y. (2016). Selection of optimal artificial boundary condition (ABC) frequencies for structural damage identification. Journal of Sound and Vibration, 374, 245-259.