Lijia Luo

1.5k total citations
83 papers, 1.3k citations indexed

About

Lijia Luo is a scholar working on Control and Systems Engineering, Mechanical Engineering and Analytical Chemistry. According to data from OpenAlex, Lijia Luo has authored 83 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Control and Systems Engineering, 34 papers in Mechanical Engineering and 20 papers in Analytical Chemistry. Recurrent topics in Lijia Luo's work include Fault Detection and Control Systems (46 papers), Mineral Processing and Grinding (25 papers) and Spectroscopy and Chemometric Analyses (20 papers). Lijia Luo is often cited by papers focused on Fault Detection and Control Systems (46 papers), Mineral Processing and Grinding (25 papers) and Spectroscopy and Chemometric Analyses (20 papers). Lijia Luo collaborates with scholars based in China, United States and New Zealand. Lijia Luo's co-authors include Shiyi Bao, Jianfeng Mao, Di Tang, Zengliang Gao, Jingqi Yuan, Chudong Tong, Yuanyuan Xu, Jingqi Yuan, Xin Peng and Junwei Sun and has published in prestigious journals such as Chemical Engineering Journal, Expert Systems with Applications and Energy.

In The Last Decade

Lijia Luo

81 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Lijia Luo China 21 789 586 265 187 155 83 1.3k
Shiyi Bao China 20 533 0.7× 559 1.0× 179 0.7× 132 0.7× 28 0.2× 81 1.0k
Zhizhong Mao China 20 1.0k 1.3× 378 0.6× 98 0.4× 79 0.4× 89 0.6× 125 1.6k
Mingxing Jia China 18 959 1.2× 604 1.0× 210 0.8× 162 0.9× 49 0.3× 79 1.2k
Bei Sun China 20 548 0.7× 380 0.6× 76 0.3× 52 0.3× 136 0.9× 105 1.2k
Jianfeng Mao China 21 420 0.5× 863 1.5× 124 0.5× 157 0.8× 21 0.1× 100 1.4k
Iori Hashimoto Japan 22 1.7k 2.1× 831 1.4× 577 2.2× 389 2.1× 165 1.1× 97 2.1k
Yuqing Chang China 18 663 0.8× 626 1.1× 139 0.5× 130 0.7× 61 0.4× 120 1.1k
Arun K. Tangirala India 16 682 0.9× 150 0.3× 85 0.3× 69 0.4× 64 0.4× 89 1.1k
Dengji Zhou China 21 498 0.6× 316 0.5× 24 0.1× 156 0.8× 92 0.6× 93 1.5k
Xuejun Li China 21 801 1.0× 773 1.3× 61 0.2× 40 0.2× 65 0.4× 134 1.5k

Countries citing papers authored by Lijia Luo

Since Specialization
Citations

This map shows the geographic impact of Lijia Luo's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Lijia Luo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lijia Luo more than expected).

Fields of papers citing papers by Lijia Luo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Lijia Luo. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Lijia Luo. The network helps show where Lijia Luo may publish in the future.

Co-authorship network of co-authors of Lijia Luo

This figure shows the co-authorship network connecting the top 25 collaborators of Lijia Luo. A scholar is included among the top collaborators of Lijia Luo based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Lijia Luo. Lijia Luo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Tong, Chudong, et al.. (2025). Joint time-serial variation analysis for fault monitoring of chemical processes. Process Safety and Environmental Protection. 196. 106867–106867. 2 indexed citations
2.
Zhen, Congmian, S. Chen, Hongchang Wang, et al.. (2025). Creep-fatigue properties and life prediction of TP321 austenitic stainless steel at high temperature. Journal of Materials Science. 60(12). 5603–5622.
3.
Luo, Lijia, et al.. (2025). Monitoring of abnormal conditions of underground pipelines using fiber-optic vibration sensing and deep learning. International Journal of Pressure Vessels and Piping. 217. 105561–105561. 1 indexed citations
4.
Luo, Lijia, et al.. (2025). Detection and evaluation of thermal aging damage in 316H stainless steel using frequency mixing nonlinear ultrasonic method. Engineering Failure Analysis. 170. 109327–109327. 1 indexed citations
5.
Chen, S., Hongchang Wang, Ling Li, et al.. (2024). Creep-fatigue interactive behavior and damage mechanism of TP321 stainless steel under hybrid-controlled conditions. Materials Characterization. 218. 114528–114528. 1 indexed citations
6.
Tong, Chudong, Long Chen, & Lijia Luo. (2024). Dynamic process monitoring based on parallel latent regressive models. Measurement Science and Technology. 35(11). 116207–116207. 1 indexed citations
7.
Luo, Lijia, et al.. (2024). A nonlinear ultrasonic wave mixing method for looseness detection of bolted joints. Ultrasonics. 142. 107402–107402. 8 indexed citations
8.
Luo, Lijia, et al.. (2023). Robust and sparse canonical correlation analysis for fault detection and diagnosis using training data with outliers. Expert Systems with Applications. 236. 121434–121434. 12 indexed citations
9.
Luo, Lijia, et al.. (2023). Tube-to-tube impact wear damage mechanism and nonlinear ultrasonic detection method of alloy 690 tubes. Engineering Failure Analysis. 156. 107821–107821. 7 indexed citations
10.
Bao, Shiyi & Lijia Luo. (2020). Monitoring of industrial processes using robust global–local preserving projection. Journal of Chemometrics. 34(9). 1 indexed citations
11.
Zhao, Shunyi, Yuriy S. Shmaliy, Choon Ki Ahn, & Lijia Luo. (2019). An Improved Iterative FIR State Estimator and Its Applications. IEEE Transactions on Industrial Informatics. 16(2). 1003–1012. 56 indexed citations
12.
Luo, Lijia, et al.. (2019). Improvements to the T2 Statistic for Multivariate Fault Detection. Industrial & Engineering Chemistry Research. 58(45). 20692–20709. 16 indexed citations
13.
Luo, Lijia, Shiyi Bao, & Jianfeng Mao. (2019). Adaptive Selection of Latent Variables for Process Monitoring. Industrial & Engineering Chemistry Research. 58(21). 9075–9086. 19 indexed citations
14.
Bao, Shiyi, Lijia Luo, Jianfeng Mao, Di Tang, & Zhenyu Ding. (2018). Robust Monitoring of Industrial Processes in the Presence of Outliers in Training Data. Industrial & Engineering Chemistry Research. 57(24). 8230–8239. 12 indexed citations
15.
Luo, Lijia, Shiyi Bao, Jianfeng Mao, & Zhenyu Ding. (2018). Industrial Process Monitoring Based on Knowledge–Data Integrated Sparse Model and Two-Level Deviation Magnitude Plots. Industrial & Engineering Chemistry Research. 57(2). 611–622. 14 indexed citations
16.
Luo, Lijia. (2018). Monitoring Uneven Multistage/Multiphase Batch Processes using Trajectory‐Based Fuzzy Phase Partition and Hybrid MPCA Models. The Canadian Journal of Chemical Engineering. 97(1). 178–187. 8 indexed citations
17.
Luo, Lijia, Shiyi Bao, Jianfeng Mao, & Di Tang. (2018). Just-in-Time Selection of Principal Components for Fault Detection: The Criteria Based on Principal Component Contributions to the Sample Mahalanobis Distance. Industrial & Engineering Chemistry Research. 57(10). 3656–3665. 9 indexed citations
18.
Luo, Lijia, Shiyi Bao, Zhenyu Ding, & Jianfeng Mao. (2017). A Variable-Correlation-Based Sparse Modeling Method for Industrial Process Monitoring. Industrial & Engineering Chemistry Research. 56(24). 6981–6992. 10 indexed citations
19.
Luo, Lijia, Shiyi Bao, Jianfeng Mao, & Di Tang. (2017). Monitoring Batch Processes Using Sparse Parallel Factor Decomposition. Industrial & Engineering Chemistry Research. 56(44). 12682–12692. 4 indexed citations
20.
Luo, Lijia, Shiyi Bao, Jianfeng Mao, & Di Tang. (2016). Fault Detection and Diagnosis Based on Sparse PCA and Two-Level Contribution Plots. Industrial & Engineering Chemistry Research. 56(1). 225–240. 40 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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