| Fault detection and diagnosis in industrial systems LH Chiang, EL Russell, RD Braatz Springer Science & Business Media, 2000 | 2660 | 2000 |
| Fault diagnosis in chemical processes using Fisher discriminant analysis, discriminant partial least squares, and principal component analysis LH Chiang, EL Russell, RD Braatz Chemometrics and intelligent laboratory systems 50 (2), 243-252, 2000 | 703 | 2000 |
| Fault diagnosis based on Fisher discriminant analysis and support vector machines LH Chiang, ME Kotanchek, AK Kordon Computers & chemical engineering 28 (8), 1389-1401, 2004 | 607 | 2004 |
| Fault detection in industrial processes using canonical variate analysis and dynamic principal component analysis EL Russell, LH Chiang, RD Braatz Chemometrics and intelligent laboratory systems 51 (1), 81-93, 2000 | 571 | 2000 |
| Advances and opportunities in machine learning for process data analytics SJ Qin, LH Chiang Computers & Chemical Engineering 126, 465-473, 2019 | 205 | 2019 |
| Exploring process data with the use of robust outlier detection algorithms LH Chiang, RJ Pell, MB Seasholtz Journal of Process Control 13 (5), 437-449, 2003 | 205 | 2003 |
| Process monitoring using causal map and multivariate statistics: fault detection and identification LH Chiang, RD Braatz Chemometrics and intelligent laboratory systems 65 (2), 159-178, 2003 | 150 | 2003 |
| Big data analytics in chemical engineering L Chiang, B Lu, I Castillo Annual review of chemical and biomolecular engineering 8, 63-85, 2017 | 138 | 2017 |
| Genetic algorithms combined with discriminant analysis for key variable identification LH Chiang, RJ Pell Journal of Process Control 14 (2), 143-155, 2004 | 131 | 2004 |
| Diagnosis of multiple and unknown faults using the causal map and multivariate statistics LH Chiang, B Jiang, X Zhu, D Huang, RD Braatz Journal of Process Control 28, 27-39, 2015 | 88 | 2015 |
| Industrial experiences with multivariate statistical analysis of batch process data LH Chiang, R Leardi, RJ Pell, MB Seasholtz Chemometrics and Intelligent Laboratory Systems 81 (2), 109-119, 2006 | 85 | 2006 |
| Industrial PLS model variable selection using moving window variable importance in projection B Lu, I Castillo, L Chiang, TF Edgar Chemometrics and Intelligent Laboratory Systems 135, 90-109, 2014 | 58 | 2014 |
| Recent trends on hybrid modeling for Industry 4.0 J Sansana, MN Joswiak, I Castillo, Z Wang, R Rendall, LH Chiang, ... Computers & Chemical Engineering 151, 107365, 2021 | 50 | 2021 |
| Industrial implementation of on-line multivariate quality control LH Chiang, LF Colegrove Chemometrics and Intelligent Laboratory Systems 88 (2), 143-153, 2007 | 49 | 2007 |
| Data-driven methods for batch data analysis–A critical overview and mapping on the complexity scale R Rendall, LH Chiang, MS Reis Computers & Chemical Engineering 124, 1-13, 2019 | 48 | 2019 |
| Semi-supervised online soft sensor maintenance experiences in the chemical industry B Lu, L Chiang Journal of Process Control 67, 23-34, 2018 | 46 | 2018 |
| 工业系统的故障检测与诊断 蒋浩天， 拉塞尔， 布拉茨， 段建民 机械工业出版社, 2003 | 46 | 2003 |
| Challenges and future research directions MS Reis, RD Braatz, LH Chiang Chemical Engineering Progress 112 (3), 46-50, 2016 | 44 | 2016 |
| Dimensionality reduction for visualizing industrial chemical process data M Joswiak, Y Peng, I Castillo, LH Chiang Control Engineering Practice 93, 104189, 2019 | 29 | 2019 |
| Robust inferential sensors based on ensemble of predictors generated by genetic programming E Jordaan, A Kordon, L Chiang, G Smits Lecture notes in computer science, 522-531, 2004 | 27 | 2004 |
Richard D. BraatzEdwin R. Gilliland Professor, Massachusetts Institute of TechnologyVerified email at mit.edu
