Mingwei Jia

489 total citations · 1 hit paper
28 papers, 279 citations indexed

About

Mingwei Jia is a scholar working on Control and Systems Engineering, Artificial Intelligence and Mechanical Engineering. According to data from OpenAlex, Mingwei Jia has authored 28 papers receiving a total of 279 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Control and Systems Engineering, 11 papers in Artificial Intelligence and 9 papers in Mechanical Engineering. Recurrent topics in Mingwei Jia's work include Fault Detection and Control Systems (25 papers), Mineral Processing and Grinding (9 papers) and Anomaly Detection Techniques and Applications (8 papers). Mingwei Jia is often cited by papers focused on Fault Detection and Control Systems (25 papers), Mineral Processing and Grinding (9 papers) and Anomaly Detection Techniques and Applications (8 papers). Mingwei Jia collaborates with scholars based in China, Taiwan and United Kingdom. Mingwei Jia's co-authors include Yi Liu, Yuan Yao, Tao Yang, Danya Xu, Zengliang Gao, Junhao Hu, Qiao Liu, Ying Zhang, Yi Liu and Haibin Zheng and has published in prestigious journals such as SHILAP Revista de lepidopterología, Industrial & Engineering Chemistry Research and Chemical Engineering Science.

In The Last Decade

Mingwei Jia

25 papers receiving 272 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Graph convolutional network soft sensor for process quality prediction

2023 82 citations Mingwei Jia, Danya Xu et al. Journal of Process Control profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mingwei Jia China	10	205	104	82	27	18	28	279
Yujia Zhao China	7	243 1.2×	97 0.9×	60 0.7×	39 1.4×	16 0.9×	14	341
Anna Bartkowiak Poland	8	181 0.9×	44 0.4×	130 1.6×	26 1.0×	17 0.9×	42	300
Ting Xue China	11	271 1.3×	58 0.6×	53 0.6×	39 1.4×	13 0.7×	25	336
Celso J. Munaro Brazil	10	234 1.1×	37 0.4×	129 1.6×	16 0.6×	12 0.7×	42	306
Jingxin Zhang China	11	281 1.4×	80 0.8×	137 1.7×	63 2.3×	61 3.4×	23	344
Lamiaa M. Elshenawy Egypt	10	240 1.2×	63 0.6×	121 1.5×	48 1.8×	48 2.7×	15	304
Sourabh Dash United States	6	257 1.3×	57 0.5×	98 1.2×	60 2.2×	36 2.0×	8	301
Gerard Escudero Spain	10	256 1.2×	201 1.9×	157 1.9×	29 1.1×	71 3.9×	18	470
Mingxi Ai China	13	99 0.5×	65 0.6×	203 2.5×	20 0.7×	6 0.3×	26	329
Viet Ha Nguyen Luxembourg	7	122 0.6×	26 0.3×	80 1.0×	19 0.7×	47 2.6×	26	312

Countries citing papers authored by Mingwei Jia

Since Specialization

Citations

This map shows the geographic impact of Mingwei Jia'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 Mingwei Jia with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mingwei Jia more than expected).

Fields of papers citing papers by Mingwei Jia

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mingwei Jia. 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 Mingwei Jia. The network helps show where Mingwei Jia may publish in the future.

Co-authorship network of co-authors of Mingwei Jia

This figure shows the co-authorship network connecting the top 25 collaborators of Mingwei Jia. A scholar is included among the top collaborators of Mingwei Jia 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 Mingwei Jia. Mingwei Jia is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Jia, Mingwei, Yuan Yao, & Yi Liu. (2025). Review on Graph Neural Networks for Process Soft Sensor Development, Fault Diagnosis, and Process Monitoring. Industrial & Engineering Chemistry Research. 64(17). 8543–8564. 7 indexed citations

Jia, Mingwei, Bingbing Shen, & Yi Liu. (2025). Graph Contrastive Learning With Adaptive Distribution Transformation for Fault Detection and Isolation Using Limited Labeled Faults. IEEE Transactions on Instrumentation and Measurement. 74. 1–13. 1 indexed citations

Jia, Mingwei, et al.. (2025). Mathematical modelling of ammonia nitrogen dynamics in a recirculating aquaculture system. Aquacultural Engineering. 111. 102594–102594.

Wang, Yan, et al.. (2025). Graph contrastive learning of modeling global-local interactions under hierarchical strategy: Application in anomaly detection. Process Safety and Environmental Protection. 196. 106871–106871. 2 indexed citations

Jia, Mingwei, et al.. (2025). Just-in-time process soft sensor with spatiotemporal graph decoupled learning. Chemometrics and Intelligent Laboratory Systems. 261. 105367–105367. 1 indexed citations

Liu, Qiao, Rong Yin, Xiaowei Guo, et al.. (2025). Locally spatiotemporal soft sensor for key indicator prediction in cement production process. Chemical Engineering Science. 307. 121386–121386. 5 indexed citations

Liu, Qiao, et al.. (2024). Two-dimensional LSTM soft sensor using noisy process data. Measurement Science and Technology. 35(8). 85001–85001. 7 indexed citations

Liu, Yi, et al.. (2024). Knowledge Distillation‐Based Zero‐Shot Learning for Process Fault Diagnosis. SHILAP Revista de lepidopterología. 7(6).

Jia, Mingwei, Le Zhou, Yi Liu, Zengliang Gao, & Yuan Yao. (2024). Global Dependency Graph Network for Soft Sensing in Process Industry. IEEE Sensors Journal. 24(16). 26290–26300. 1 indexed citations

10.

Jia, Mingwei, et al.. (2024). Temporal graph convolutional network soft sensor for molecular weight distribution prediction. Chemometrics and Intelligent Laboratory Systems. 252. 105196–105196. 4 indexed citations

11.

Jia, Mingwei, Chao Yang, Qiang Liu, Zengliang Gao, & Yi Liu. (2024). Semisupervised Graph Contrastive Learning for Process Fault Diagnosis. Industrial & Engineering Chemistry Research. 63(33). 14712–14726. 5 indexed citations

12.

Liu, Yi, Mingwei Jia, Danya Xu, Tao Yang, & Yuan Yao. (2024). Physics-guided graph learning soft sensor for chemical processes. Chemometrics and Intelligent Laboratory Systems. 249. 105131–105131. 20 indexed citations

13.

Jia, Mingwei, et al.. (2024). Physical-anchored graph learning for process key indicator prediction. Control Engineering Practice. 154. 106167–106167. 11 indexed citations

14.

Jia, Mingwei, et al.. (2024). Adversarial relationship graph learning soft sensor via negative information exclusion. Journal of Process Control. 145. 103354–103354. 6 indexed citations

15.

Jia, Mingwei, et al.. (2023). Domain adaptation graph convolution network for quality inferring of batch processes. Chemometrics and Intelligent Laboratory Systems. 243. 105028–105028. 10 indexed citations

16.

Jia, Mingwei, Junhao Hu, Yi Liu, Zengliang Gao, & Yuan Yao. (2023). Topology-Guided Graph Learning for Process Fault Diagnosis. Industrial & Engineering Chemistry Research. 62(7). 3238–3248. 34 indexed citations

17.

Jia, Mingwei, et al.. (2023). Transductive transfer broad learning for cross-domain information exploration and multigrade soft sensor application. Chemometrics and Intelligent Laboratory Systems. 235. 104778–104778. 9 indexed citations

18.

Jia, Mingwei, Danya Xu, Tao Yang, Yuan Yao, & Yi Liu. (2023). Dynamic Graph Learning Soft Sensor in Process Industry. 1 indexed citations

19.

Jia, Mingwei, Danya Xu, Tao Yang, Yi Liu, & Yuan Yao. (2023). Graph convolutional network soft sensor for process quality prediction. Journal of Process Control. 123. 12–25. 82 indexed citations breakdown →

20.

Liu, Qiao, et al.. (2022). Correntropy long short term memory soft sensor for quality prediction in industrial polyethylene process. Chemometrics and Intelligent Laboratory Systems. 231. 104678–104678. 22 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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