（一）数据驱动的闭环过程故障诊断技术：系统性地分析了反馈控制对经典数据驱动故障诊断技术的影响，提出了以反馈不变量及输出过采样为代表的解决方案. 代表论文：
1. Kai Wang, Junghui Chen*, Zhihuan Song*, .“Performance analysis of dynamic PCA for closed-Loop process monitoring and its improvement by output oversampling scheme.” IEEE Transactions on Control Systems Technology, 2019,27(1) :378-385.
2. Kai Wang, Junghui Chen*, Zhihuan Song*.”Data-driven sensor fault diagnosis systems for linear feedback control loops.” Jounal of Process Control,2017, 54 : 152-171.
3. Kai Wang, Junghui Chen*,Zhihuan Song*.”A new excitation scheme for closed-loop subspace identification using additional sampling outputs and its extension to instrumental variable method.”Journal of the Franklin Institute, 2018, 355(14) ；6675-6692.
4. Kai Wang, Junghui Chen*,Zhihuan Song*.“Fault diagnosis for processes with feedback control loops by shifed output sampling approach.” Journal of the Franklin Institute, 2018,355(7) : 3249-3273.
（二）复杂动态过程建模与应用，如动态过程数据的模态识别与分割，动态批次过程监测等. 代表论文：
1. Kai Wang, Junghui Chen*,Zhihuan Song*.“Concurrent Fault Detection and Anomaly Location in Closed-Loop Dynamic Systems with Measured Disturbances.”IEEE Transactions on Automation Science and Engineering, 2018 (Online)
2. Kai Wang, Junghui Chen*, Zhihuan Song*, .”Using Multivariate Pattern Segmentation to Assess Process Performance and Mine Good Operation Conditions for Dynamic Chemical Industry.” Chemical Engineering Science, 2019，201，339-348
3. Kai Wang, Bhushan Gopaluni,Junghui Chen*,Zhihuan Song*.“Data-Driven Dynamic Modeling and Online Monitoring for Multiphase and Multimode Batch Processes with Uneven Batch Durations.” Industrial & Engineering Chemistry Research (Online)
（三）深度学习在工业智能相关的应用. 代表论文：
1. Kai Wang, Bhushan Gopaluni,Junghui Chen*, Zhihuan Song*.“Deep Learning of Complex Batch Process Data and Its Application on Quality Prediction.” IEEE Transactions on Industrial Informatics,2018(Online)
2. Kai Wang, Michael Forbes, Bhushan Gopaluni, Junghui Chen*, Zhihuan Song*.”Systematical Development of a New Variational Autoencoder Model Based on Uncertainty Data for Monitoring Nonlinear Processes” IEEE Access,7 (2019): 22554-22565.
3. Weiming Shao, Zhiqiang Ge, Zhihuan Song,Kai Wang, Nonlinear industrial soft sensor development based on semi-supervised probabilistic mixture of extreme learning machines. Control Engineering Practice,2019,91,104098