Husnain Ali

450 total citations
29 papers, 248 citations indexed

About

Husnain Ali is a scholar working on Control and Systems Engineering, Mechanical Engineering and Statistics, Probability and Uncertainty. According to data from OpenAlex, Husnain Ali has authored 29 papers receiving a total of 248 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Control and Systems Engineering, 13 papers in Mechanical Engineering and 4 papers in Statistics, Probability and Uncertainty. Recurrent topics in Husnain Ali's work include Fault Detection and Control Systems (12 papers), Mineral Processing and Grinding (9 papers) and Advanced Statistical Process Monitoring (3 papers). Husnain Ali is often cited by papers focused on Fault Detection and Control Systems (12 papers), Mineral Processing and Grinding (9 papers) and Advanced Statistical Process Monitoring (3 papers). Husnain Ali collaborates with scholars based in Hong Kong, China and Pakistan. Husnain Ali's co-authors include Furong Gao, Zheng Zhang, Yuan Yao, Haslinda Zabiri, Abdulhalim Shah Maulud, Le Yao, Yuanqiang Zhou, Syed Ali Ammar Taqvi, Humbul Suleman and Lukman Ismail and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Industrial & Engineering Chemistry Research.

In The Last Decade

Husnain Ali

24 papers receiving 240 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Husnain Ali Hong Kong 10 111 91 49 45 15 29 248
Sourabh Dash United States 6 257 2.3× 98 1.1× 57 1.2× 60 1.3× 36 2.4× 8 301
Celso J. Munaro Brazil 10 234 2.1× 129 1.4× 37 0.8× 16 0.4× 12 0.8× 42 306
Alberto Prieto-Moreno Cuba 8 213 1.9× 120 1.3× 54 1.1× 42 0.9× 38 2.5× 15 294
Luping Zhao China 14 288 2.6× 227 2.5× 27 0.6× 64 1.4× 63 4.2× 50 368
Viet Ha Nguyen Luxembourg 7 122 1.1× 80 0.9× 26 0.5× 19 0.4× 47 3.1× 26 312
Hiranmayee Vedam United States 8 284 2.6× 108 1.2× 33 0.7× 110 2.4× 36 2.4× 9 315
Jingde Wang China 10 160 1.4× 96 1.1× 30 0.6× 22 0.5× 25 1.7× 36 239
Raphael T. Samuel United Kingdom 5 359 3.2× 213 2.3× 72 1.5× 65 1.4× 101 6.7× 7 384
Manxi Lin Denmark 3 226 2.0× 132 1.5× 30 0.6× 8 0.2× 4 0.3× 7 273

Countries citing papers authored by Husnain Ali

Since Specialization
Citations

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

Fields of papers citing papers by Husnain Ali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Husnain Ali

This figure shows the co-authorship network connecting the top 25 collaborators of Husnain Ali. A scholar is included among the top collaborators of Husnain Ali 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 Husnain Ali. Husnain Ali 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.
Ding, Jian, et al.. (2025). Robust optimal iterative learning control for constrained batch processes with nonuniform batch lengths. The Canadian Journal of Chemical Engineering. 103(9). 4343–4359. 2 indexed citations
2.
Ali, Husnain & Furong Gao. (2025). Fault Detection and Diagnosis using Reconstruction-based DiGLPP: Application to Industrial Distillation System. IFAC-PapersOnLine. 59(6). 187–192. 2 indexed citations
3.
Ali, Husnain, et al.. (2025). Fast soft sensor model migration in injection molding processes: A reconstruction based deep learning framework. Chemical Engineering Science. 320. 122634–122634.
4.
Ali, Husnain, et al.. (2025). Adaptive transfer learning with C-P-T sensor fusion for few-shot anomaly diagnosis in injection molding process. Chemical Engineering Science. 320. 122562–122562. 1 indexed citations
5.
Ali, Husnain, Rizwan Safdar, Jinfeng Liu, et al.. (2025). Hybrid Fusion Paradigm in Advanced Process Monitoring: A Panoramic Review and Future Perspectives. Industrial & Engineering Chemistry Research. 64(47). 22465–22514.
6.
Ali, Husnain, Rizwan Safdar, Jinfeng Liu, et al.. (2025). Process monitoring and dynamic fusion of complex industrial systems: A reconstruction-based Bayesian framework. Computers & Chemical Engineering. 203. 109352–109352. 2 indexed citations
7.
Ali, Husnain, Rizwan Safdar, Yuanqiang Zhou, et al.. (2025). Intelligent machine learning-based multi-model fusion monitoring: application to industrial physio-chemical systems. Control Engineering Practice. 162. 106361–106361. 10 indexed citations
8.
Ali, Husnain, et al.. (2025). A correction symbol Granger causality approach to root cause diagnosis of non-stationary industrial processes. Computers & Chemical Engineering. 205. 109479–109479.
9.
Rasool, Muhammad Hammad, et al.. (2025). Mitigating shale swelling in deep drilling: Novel natural deep eutectic solvent vs hybrid additives system. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 2(2). 100173–100173. 3 indexed citations
10.
Ali, Husnain, et al.. (2024). Assessing the Renal Outcomes of Semaglutide in Diabetic Kidney Disease: A Systematic Review. Cureus. 16(7). e64038–e64038. 3 indexed citations
11.
Ali, Husnain, Yuanqiang Zhou, Yuan Yao, et al.. (2024). Robust statistical industrial fault monitoring: A machine learning-based distributed CCA and low frequency control charts. Chemical Engineering Science. 299. 120460–120460. 24 indexed citations
12.
Ali, Husnain, et al.. (2024). Advance industrial monitoring of physio-chemical processes using novel integrated machine learning approach. Journal of Industrial Information Integration. 42. 100709–100709. 20 indexed citations
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14.
Rasool, Muhammad Hammad, Maqsood Ahmad, Numair Ahmed Siddiqui, & Husnain Ali. (2024). Novel application of citric acid based natural deep eutectic solvent in drilling fluids for shale swelling prevention. Scientific Reports. 14(1). 25729–25729. 8 indexed citations
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Ali, Husnain, Rizwan Safdar, Yuanqiang Zhou, et al.. (2024). A novel dynamic machine learning-based explainable fusion monitoring: application to industrial and chemical processes. Machine Learning Science and Technology. 6(1). 15005–15005. 14 indexed citations
18.
Ali, Husnain, et al.. (2024). Novel deep learning based soft sensor feature extraction for part weight prediction in injection molding processes. Journal of Manufacturing Systems. 78. 58–68. 8 indexed citations
19.
Ali, Husnain, Zheng Zhang, & Furong Gao. (2023). Multiscale monitoring of industrial chemical process using wavelet-entropy aided machine learning approach. Process Safety and Environmental Protection. 180. 1053–1075. 33 indexed citations
20.
Ali, Husnain, et al.. (2022). Fault diagnosis by using multi-scale signed directed graph. AIP conference proceedings. 2472. 40002–40002. 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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