Minglei Yang

2.1k total citations
75 papers, 1.7k citations indexed

About

Minglei Yang is a scholar working on Control and Systems Engineering, Mechanical Engineering and Analytical Chemistry. According to data from OpenAlex, Minglei Yang has authored 75 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Control and Systems Engineering, 18 papers in Mechanical Engineering and 14 papers in Analytical Chemistry. Recurrent topics in Minglei Yang's work include Fault Detection and Control Systems (17 papers), Process Optimization and Integration (17 papers) and Advanced Control Systems Optimization (13 papers). Minglei Yang is often cited by papers focused on Fault Detection and Control Systems (17 papers), Process Optimization and Integration (17 papers) and Advanced Control Systems Optimization (13 papers). Minglei Yang collaborates with scholars based in China, Norway and Canada. Minglei Yang's co-authors include Yi‐An Zhu, Zhi‐Jun Sui, De Chen, Xinggui Zhou, Fan Chen, Xinggui Zhou, Junwu Zhu, Yingda Yu, Feng Qian and Anders Holmen and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and ACS Catalysis.

In The Last Decade

Minglei Yang

69 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Minglei Yang China 19 1.1k 999 388 290 216 75 1.7k
Л. Дімітров Bulgaria 23 860 0.8× 305 0.3× 364 0.9× 422 1.5× 85 0.4× 127 1.4k
Jakob Burger Germany 21 981 0.9× 806 0.8× 141 0.4× 388 1.3× 431 2.0× 79 2.1k
Dan Wu China 29 792 0.7× 234 0.2× 303 0.8× 461 1.6× 322 1.5× 151 2.5k
Jon Paul Janet Sweden 23 1.6k 1.4× 236 0.2× 528 1.4× 139 0.5× 30 0.1× 45 2.2k
Martin Holeňa Czechia 18 864 0.8× 805 0.8× 131 0.3× 139 0.5× 48 0.2× 103 1.6k
Wenbo Gao China 25 1.6k 1.5× 1.9k 1.9× 174 0.4× 98 0.3× 49 0.2× 87 2.8k
Jian–wei Liu China 20 545 0.5× 164 0.2× 193 0.5× 105 0.4× 114 0.5× 94 1.2k
Loı̈c M. Roch Switzerland 19 1.3k 1.2× 111 0.1× 124 0.3× 114 0.4× 87 0.4× 36 2.2k
Geun Ho Gu South Korea 21 1.2k 1.1× 475 0.5× 132 0.3× 201 0.7× 22 0.1× 47 1.9k
Milad Abolhasani United States 33 1.6k 1.4× 111 0.1× 141 0.4× 258 0.9× 153 0.7× 118 3.4k

Countries citing papers authored by Minglei Yang

Since Specialization
Citations

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

Fields of papers citing papers by Minglei Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Minglei Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Minglei Yang. A scholar is included among the top collaborators of Minglei Yang 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 Minglei Yang. Minglei Yang 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.
Wang, Yeqin, Minglei Yang, & Yafeng Wang. (2025). Bounded UDE-Based Robust Control for MIMO Systems Based on a Nonlinear Design of Error Dynamics. IEEE Journal of Emerging and Selected Topics in Industrial Electronics. 6(4). 1756–1765.
2.
3.
Yang, Minglei, et al.. (2024). A deep reinforcement learning approach to gasoline blending real-time optimization under uncertainty. Chinese Journal of Chemical Engineering. 71. 183–192. 3 indexed citations
4.
Zhu, Jiannan, et al.. (2024). A semi-supervised learning algorithm for high and low-frequency variable imbalances in industrial data. Computers & Chemical Engineering. 193. 108933–108933.
5.
Yang, Minglei, et al.. (2024). An ADMM-based low-complexity algorithm for atomic norm minimization in DOA estimation. IET conference proceedings.. 2023(47). 1277–1283. 1 indexed citations
6.
Yang, Minglei, et al.. (2024). Refined coherent parameters estimation based on iterative Chirp-Z transform for DCAR on moving platforms. IET conference proceedings.. 2023(47). 221–226. 1 indexed citations
7.
Zhu, Jiannan, et al.. (2023). Data-driven models of crude distillation units for production planning and for operations monitoring. Computers & Chemical Engineering. 177. 108322–108322. 9 indexed citations
8.
He, Wangli, et al.. (2023). Data-driven two-stage distributionally robust optimization for refinery planning under uncertainty. Chemical Engineering Science. 269. 118466–118466. 9 indexed citations
9.
Zhao, Liang, et al.. (2023). Data-driven worst case model predictive control algorithm for propylene distillation column under uncertainty of top composition. Journal of Process Control. 124. 199–213. 2 indexed citations
10.
Long, Jian, Yifan Chen, Deng‐Ke Cao, Pengyu Chen, & Minglei Yang. (2023). Yield and Properties Prediction Based on the Multicondition LSTM Model for the Solvent Deasphalting Process. ACS Omega. 8(6). 5437–5450. 6 indexed citations
11.
Liu, Tianbo, et al.. (2023). Online Determination on the Properties of Naphtha as the Ethylene Feedstock Using Near-Infrared Spectroscopy. Petroleum Chemistry. 63(9). 1069–1079.
12.
Yu, Huijing, Wenli Du, Minglei Yang, et al.. (2023). A Novel Interpretable Ensemble Learning Method for NIR-Based Rapid Characterization of Petroleum Products. IEEE Transactions on Instrumentation and Measurement. 72. 1–11. 8 indexed citations
13.
Yang, Minglei, et al.. (2022). Process modelling, optimisation and analysis of heat recovery energy system for petrochemical industry. Journal of Cleaner Production. 381. 135133–135133. 17 indexed citations
14.
Yang, Minglei, et al.. (2021). Simultaneous Optimization and Heat Integration of an Aromatics Complex with a Surrogate Model. Industrial & Engineering Chemistry Research. 60(9). 3633–3647. 5 indexed citations
15.
Yang, Minglei, et al.. (2021). Merged-Sampling Mask R-CNN With Random Proposal Expansion for Particle Measurement of SEM Images of Molecular Sieve Catalysts. IEEE Transactions on Instrumentation and Measurement. 70. 1–13. 7 indexed citations
16.
Du, Wei, et al.. (2021). Adaptive Weighted Hybrid Modeling of Hydrocracking Process and Its Operational Optimization. Industrial & Engineering Chemistry Research. 60(9). 3617–3632. 16 indexed citations
17.
Mahalec, Vladimir, et al.. (2020). Modeling the Hydrocracking Process with Deep Neural Networks. Industrial & Engineering Chemistry Research. 59(7). 3077–3090. 36 indexed citations
18.
Long, Jian, et al.. (2018). Hybrid Strategy Integrating Variable Selection and a Neural Network for Fluid Catalytic Cracking Modeling. Industrial & Engineering Chemistry Research. 58(1). 247–258. 33 indexed citations
19.
Zhong, Weimin, et al.. (2017). A New Lumped Kinetic Model of an Industrial Hydrocracking Process. SHILAP Revista de lepidopterología. 9 indexed citations
20.
Wei, Min, Minglei Yang, Feng Qian, et al.. (2017). Dynamic Modeling and Economic Model Predictive Control with Production Mode Switching for an Industrial Catalytic Naphtha Reforming Process. Industrial & Engineering Chemistry Research. 56(31). 8961–8971. 13 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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