1993年-2000年 山东曲阜师范大学 学士、硕士
2000年-2003年 上海交通大学 博士
2003年-2005年 清华大学，自动化系，博士后
2005年-2008年 清华大学，自动化系，助理研究员
2006年12月-2008年3月 德国洪堡学者
2008年-至今 清华大学，自动化系，副教授
Moral Robots：
以紧急疏散、公共物品博弈为场景，借助脑电分析与机器人群平台，综合行为认知与脑科学等学科，研究机器人的道德认知问题。
Automation Theory of Automation Science：
未来将实现：（1）在人类最少干预下，机器人如何自动分析、设计和实现以故障诊断为代表的自动化方法？（2）建立适用于故障诊断分析与设计的人-机交互系统。
国家重点研发计划一级课题（2020YFF0304904），人-车-路协同疏导与管控技术研究及应用示范,2020-2022，负责人
国家重点研发计划一级课题（2018YFC0809301），2018-2020，负责人
国家自然科学基金面上项目, 大数据驱动的故障检测：改进的PCA与PLS方，2019-2022，负责人
国家自然科学基金面上项目，受物理安全感知约束的群系统协同编队，2015-2018，负责人
国家自然科学基金委重大项目，高速列车信息控制系统实时故障诊断与应用验证，2015-2019，参加者
国家自然科学基金委重大项目，大型高炉非正常工况诊断与安全运行方法及实现技术，2013-2017，参加者
**973项目子课题，2011-2014，参加者
973项目一级课题，飞行器威胁目标识别与图像鲁棒匹配理论与方法，2010-2014，参加者
国家自然科学基金创新研究群体，复杂系统控制与信息处理中的若干关键问题研究与应用，2011-2013，参加者
国家自然科学基金重点项目，复杂工程系统故障预测与预测维护理论及关键技术研究，2008-2011，参加者
国家自然科学基金青年基金，基于动态优化策略的复杂网络研究，2009-2011，负责人
2019年度中国自动化学会自然科学奖二等奖（排名第一）
2011年度中国自动化学会自然科学奖一等奖
2011年度上海市自然科学奖三等奖
2007-2008年，德国洪堡基金
2005年清华大学优秀博士后
2005年上海市优秀博士论文
代表性期刊论文
[1] Liu D., Wang M., Chen M. Feature Ensemble Net: A Deep Framework for Detecting Incipient Faults in Dynamical Processes. IEEE Transactions on Industrial Informatics, 2022, Accepted
[2] Wang M., Zhou D., Chen M. Recursive Hybrid Variable Monitoring for Fault Detection in Nonstationary Industrial Processes. IEEE Transactions on Industrial Informatics, 2022, Accepted
[3] Zhang J., Zhou D., Chen M., Hong X. Continual learning for multimode dynamic process monitoring with applications to an ultra-supercritical thermal power plant. IEEE Transactions on Automation Science and Engineering, 2022, Accepted，
[4] Zhang J., Zhou D., Chen M. Adaptive cointegration analysis and modified RPCA with continual learning ability for monitoring multimode nonstationary processes. IEEE Transactions on Cybernetics. DOI: 10.1109/TCYB.2021.3140065,2022
[5] Wang M, Sheng L, Zhou D(*), Chen M(*). A Feature Weighted Mixed Naive Bayes Model for Monitoring Anomalies in the Fan System of a Thermal Power Plan. IEEE/CAA Journal of Automatica Sinica, 2022, in press
[6] Wu D., Sheng L., Zhou D., Chen M. Dynamic stationary subspace analysis for monitoring nonstationary dynamic processes. Industrial & Engineering Chemistry Research, 2022, accepted
[7] Wu D., Zhou D., Chen M. Performance-Driven Component Selection in the Framework of PCA for Process Monitoring: A Dynamic Selection Approach. IEEE Transactions on Control Systems Technology, DOI: 10.1109/TCST.2021.3094512
[8] Wu D., Zhou D., Chen M. Probabilistic Stationary Subspace Analysis for Monitoring Nonstationary Industrial Processes with Uncertainty. IEEE Transactions on Industrial Informatics, 18 (2022) 3114-3125.
[9] Zhang J., Chen M., Hong X. Nonlinear process monitoring using a mixture of probabilistic PCA with clusterings. Neurocomputing，DOI: 10.1016/j.neucom. 2021. 06.039, 2022
[10] Shang J., Chen M., Chen T. Optimal Linear Encryption Against Stealthy Attacks on Remote State Estimation. IEEE Transactions on Automatic Control, 66(2021) 3592-3607
[11] Zhang J., Zhou D, Chen M. Monitoring multimode processes: a modified PCA algorithm with continual learning ability. Journal of Process Control, 103 (2021) 76-86
[12] Wu D., Zhou D., Chen M. Output-relevant common trend analysis for KPI-related nonstationary process monitoring with applications to thermal power plants. IEEE Transactions on Industrial Informatics 17 (2021) 6664–6675
[13] Zhang H., Jia C., Chen M. Remaining Useful Life Prediction for Degradation Processes with Dependent and Non-Stationary Increments. IEEE Transactions on Instrumentation & Measurement,70 (2021) 3519212
[14] Zhang H., Chen M., Shang J., et al. Stochastic Process-based Degradation Modeling and RUL Prediction: From Brownian Motion to Fractional Brownian Motion. Science China 64 (2021) 171201
[15] Liu D., Shang J., Chen M. PCA-based Ensemble Detector for Incipient Faults in Dynamic Processes. IEEE Transactions on Industrial Informatics, 17 (2021) 5391- 5401
[16] Li J., Zheng X., Chen M. Height map-based social force model for stairway evacuation. Safety Science 133 (2021) 105027.
[17] Sang J., Zhang J., Zhou D., Chen M., Tai X. Incipient Fault Detection for Air Brake System of High-speed Trains. IEEE Transactions on Control Systems Technolgoy, 29 (2021) 2026 – 2037
[18] Wu D., Zhou D., Zhang J., Chen M. Multimode process monitoring based on fault dependent variable selection and moving window-negative log likelihood probability. Comput. Chem. Eng. 136 (2020) 106787.
[19] Wu D., Sheng L., Zhou D., Chen M. Dynamic stationary subspace analysis for monitoring nonstationary dynamic processes. Industrial & Engineering Chemistry Research 59 (2020) 20787–2079
[20] Wang M., Zhou D., Chen M. Wang Y. Anomaly Detection in the Fan System of a Thermal Power Plant Monitored by Continuous and Two-valued Variables, Control Engineering Practice 102 (2020) 1045222020
[21] Sang J., Zhang J., Guo T., Zhou D., Chen M., Tai X. Detection of incipient faults in EMU braking system based on data domain description and variable control limit, Neurocomputing 383 (2020) 348-358
[22] Wang Y., Zhou D. Chen M., Wang M. Weighted part mutual information related component analysis for quality-related process monitoring, Journal of Process Control 88 (2020) 111-123
[23] Zhang J, Chen M, Chen H, Hong H, Zhou D. Process monitoring based on orthogonal locality preserving projection with maximum likelihood estimation. Industrial & Engineering Chemistry Research 58 (2019) 5579-5587
[24] Shang J., Zhou D., Chen M. Incipient sensor fault diagnosis in multimode processes using conditionally independent Bayesian learning based recursive transformed component statistical analysis, Journal of Process Control 77 (2019) 7-19
[25] Zhang H., Zhou D., Chen M., Shang J. FBM-based remaining useful life prediction for degradation processes with long-range dependence and multiple modes, IEEE Transactions on Reliability 68 (2019) 1021-1033
[26] Guo T., Zhou D., Zhang J., Chen M., Tai X., Fault detection based on robust characteristic dimensionality reduction, Control Engineering Practice 84 (2019) 125-138
[27] Zhang H., Zhou D., Chen M., Xi. X. Predicting remaining useful life based on a generalized degradation with fractional Brownian motion. Mechanical Systems and Signal Processing 115 (2019) 736–752
[28] Xi X., Chen M., Zhang H., Zhou D. An improved non-Markovian degradation model with long-term dependency and item-to-item uncertainty. Mechanical Systems and Signal Processing 105 (2018) 467–480
[29] Shang J., Chen M., Zhang HW., et al. Increment-based recursive transformed component statistical analysis for monitoring blast furnace iron-making processes: An index-switching scheme, Control Engineering Practice 77 (2018) 190–200
[30] Chen M., Jiang Y., Zhou D. Decentralized Maintenance for Multi-state Systems with Heterogeneous Components, IEEE Transactions on Reliability 67 (2018) 701-714
[31] Xi X., Chen M., Zhou D. Remaining useful life prediction for multi-component systems with hidden dependencies. Science China Information Sciences, 105 (2018) 467-480
[32] Shang J., Chen M., Zhang H. Fault detection based on augmented kernel Mahalanobis distance for nonlinear dynamic processes. Computers & Chemical Engineering 109 (2018) 311–321
[33] Shang J., Chen M., Ji H., Zhou D. Isolating incipient sensor fault based on recursive transformed component statistical analysis. Journal of Process Control 64 (2018) 112-122
[34] Chen M., Shang J. Recursive Spectral Meta-Learner for online combining different fault classifiers. IEEE Transactions on Automatic Control 63 (2018) 586-593
[35] Shang J., Chen M. Dynamic Transformed Component Statistical Analysis for Fault Detection in Dynamic Processes. IEEE Transactions on Industrial Electronics 65 (2018) 578–588
[36] Zhang H., Chen M., Xi X., Zhou D. Remaining Useful Life Prediction for Degradation Processes with Long-range Dependence, IEEE Transactions on Reliability 66 (2017) 1368-1379
[37] Xi X., Chen M., Zhou D. Remaining Useful Life Prediction for Degradation Processes with Memory Effects, IEEE Transactions on Reliability 66 (2017) 751-760
[38] Shang J., Chen M., Zhou D. Dominant trend based logistic regression for fault diagnosis in non-stationary processes. Control Engineering Practice 66 (2017) 156–168
[39] Shang J., Chen M., Ji H., Zhou D. Recursive Transformed Component Statistical Analysis for Incipient Fault Detection. Automatica 80 (2017) 313-327
[40] Zhao L., Chen M., Zhou D. General (N,T,tau) Opportunistic Maintenance for mutlicomponent systems with evident and hidden failures. IEEE Transactions on Reliability 65 (2016) 1298-1312
[41] Zhang X., Chen M., Wang L. Distributed event-triggered consensus in multi-agent systems with non-linear protocols. IET Control Theory and Applications 9 (2015) 2626-2633
[42] Zhang X., Chen M., Wang L. Pang Z., Zhou D. Connection-graph-based event-triggered output consensus in multi-agent systems with time-varying couplings. IET Control Theory and Applications 9 (2015) 1-9
[43] Liu Q., Chen M., Zhou D. Single image haze removal via depth-based contrast stretching transform. Sciences China: Information Sciences 58 (2015) 012102
[44] Chen M., Xu G., Yan R., Ding S., Zhou D. Detecting scalar intermittent faults in linear stochastic dynamic systems. International Journal of Systems Sciences 46 (2015) 1337-1348
[45] Ning C., Chen M., Zhou D. Hidden Markov Model-Based Statistics Pattern Analysis for Multimode Process Monitoring: An Index-Switching Scheme. Industrial & Engineering Chemistry Research 53 (2014) 11084-11095
[46] Pang Z., Liu G., Zhou D., Chen M. Output Tracking Control for Networked Systems A Model-Based Prediction Approach. IEEE Transactions on Industrial Electronics 61 (2014) 4867-4877
[47] Chen M., Fan H., Hu C., Zhou D. Maintaining Partially Observed Systems With Imperfect Observation and Resource Constraint. IEEE Transactions on Reliability 63 (2014) 881-890
[48] Lin Y., Chen M., Zhou D. Online probabilistic operational safety assessment of multi-mode engineering systems using Bayesian methods. Reliability Engineering & System Safety 119 (2013) 150–157
[49] Si X., Chen M., Wang W., Hu C., Zhou D. Specifying measurement errors for required lifetime estimation performance. European Journal of Operational Research 231 (2013) 631-644
[50] Wei M., Chen M., Zhou D. Multi-sensor information based remaining useful life prediction with anticipated performance. IEEE Transactions on Reliability 62 (2013) 183-198
[51] Si X., Wang W., Chen M., Hu C., Zhou D., A degradation path-dependent approach for remaining useful life estimation with an exact yet closed-form solution. European Journal of Operational Research 226 (2013) 53-26
[52] Si X., Wang W., Hu C., Chen M., Zhou D. A Wiener-process based degradation model with a recursive filter algorithm for remaining useful life estimation. Mechanical Systems and Signal Processing 35 (2013) 219–237
[53] Chen M., Xu C., Zhou D. Maintaining systems with dependent failure modes and resource constraints. IEEE Transactions on Reliability 61 (2012) 440-451
[54] Lu X., Chen M., Liu M., Zhou D. Optimal imperfect periodic preventive maintenance for systems in the time-varying environment. IEEE Transactions on Reliability 61 (2012) 378-388
[55] Zhu F., Xu J., Chen M. The combination of high-gain sliding mode observers used as receivers in secure communication, IEEE Transactions on Circuits and Systems I: Regular Papers 59 (2012) 2702-2712
[56] Lu X., Chen M., Zhou D. Exact results on the statistically expected total cost and optimal solutions for extended periodic imperfect preventive maintenance. IEEE Transactions on Reliability 61 (2012) 426-439
[57] Fan H., Hu C., Chen M., Zhou D. Cooperative predictive maintenance of systems with dependent failure modes and resource constraint. IEEE Transactions on Reliability. 60 (2011) 144-157.
[58] Zhou Z., Hu C., Xu D., Chen M., Zhou D. A model for real-time failure prognosis based on hidden Markov model and belief rule base. European Journal of Operations Research 207 (2010) 269-283.
[59] Chen M., Synchronization in complex dynamical networks with random sensor delay. IEEE Trans. Circuits and Systems Part II. 57 (2010) 46-50.
[60] Shang Y., Chen M., Kurths, J. Generalized synchronization of complex networks. Phys Rev E.80 (2009) 027201.
[61] Li P., Chen M., Wu Y., Kurths J. Matrix measure criterion for synchronization in coupled map networks. Physical Review E 79 (2009) 067102
[62] Chen M., Shang Y., Zou Y. Kurths J. Synchronization in the Kuramoto model: A dynamical gradient network approach. Phys. Rev. E 77 (2008) 027101.
[63] Chen M. Chaos synchronization in complex networks. IEEE Trans. on Circuits and Syst. I: Regular Paper. 55 (2008) 1335.
[64] Chen M. Synchronization in time-varying networks: a matrix measure approach. Phys. Rev. E 76 (2007) 016104.
[65] Chen M., Kurths J. Chaos synchronization and parameter estimation from a scalar output signal. Phys. Rev. E 76 (2007) 027203.
[66] Chen M., Kurths J. Synchronization of time-delayed systems. Phys. Rev. E 76 (2007) 036212.
[67] Chen M., Zhou D. Synchronization in uncertain complex networks. Chaos 16 (2006) 013101.
[68] Chen M. Some simple synchronization criteria for complex dynamical networks. IEEE Trans. on Circuits and Syst. II: Express Brief 53 (2006) 1185.
开设课程：运筹学（研究生课）
