Mumtaz Ali

6.7k total citations · 2 hit papers
210 papers, 4.8k citations indexed

About

Mumtaz Ali is a scholar working on Management Science and Operations Research, Environmental Engineering and Artificial Intelligence. According to data from OpenAlex, Mumtaz Ali has authored 210 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Management Science and Operations Research, 55 papers in Environmental Engineering and 42 papers in Artificial Intelligence. Recurrent topics in Mumtaz Ali's work include Multi-Criteria Decision Making (44 papers), Hydrological Forecasting Using AI (42 papers) and Energy Load and Power Forecasting (29 papers). Mumtaz Ali is often cited by papers focused on Multi-Criteria Decision Making (44 papers), Hydrological Forecasting Using AI (42 papers) and Energy Load and Power Forecasting (29 papers). Mumtaz Ali collaborates with scholars based in Australia, Pakistan and Iraq. Mumtaz Ali's co-authors include Florentín Smarandache, Ramendra Prasad, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Lê Hoàng Sơn, Ravinesh C. Deo, Yong Xiang, İrfan Deli̇, Mehdi Jamei, Masoud Karbasi and Nathan Downs and has published in prestigious journals such as SHILAP Revista de lepidopterología, Renewable and Sustainable Energy Reviews and The Science of The Total Environment.

In The Last Decade

Mumtaz Ali

185 papers receiving 4.6k citations

Hit Papers

Evaluation and Prediction of Groundwater Quality for Irri... 2023 2026 2024 2025 2023 2025 25 50 75 100

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mumtaz Ali Australia 42 1.3k 1.2k 1.1k 835 728 210 4.8k
Changhua Hu China 34 734 0.6× 1.8k 1.5× 339 0.3× 843 1.0× 176 0.2× 162 6.4k
Christine A. Shoemaker United States 41 514 0.4× 1.1k 0.9× 1.8k 1.6× 301 0.4× 952 1.3× 177 6.5k
Shahab S. Band Taiwan 46 215 0.2× 1.5k 1.3× 842 0.7× 862 1.0× 744 1.0× 196 6.3k
Jianzhong Zhou China 34 312 0.2× 1.2k 1.0× 467 0.4× 1.7k 2.0× 298 0.4× 127 4.4k
Sancho Salcedo‐Sanz Spain 50 565 0.4× 3.5k 3.0× 1.4k 1.2× 3.6k 4.3× 644 0.9× 371 9.5k
Hui Qin China 40 253 0.2× 906 0.8× 779 0.7× 2.1k 2.5× 723 1.0× 144 4.2k
Francisco Martínez‐Álvarez Spain 33 581 0.4× 1.6k 1.4× 528 0.5× 1.0k 1.2× 589 0.8× 115 4.2k
Lucien Duckstein United States 35 1.6k 1.2× 453 0.4× 869 0.8× 114 0.1× 1.3k 1.7× 212 5.1k
Dalibor Petković Serbia 48 355 0.3× 2.1k 1.8× 1.2k 1.1× 2.4k 2.8× 668 0.9× 172 6.7k
D. Nagesh Kumar India 44 364 0.3× 412 0.4× 1.7k 1.5× 398 0.5× 2.6k 3.5× 164 6.1k

Countries citing papers authored by Mumtaz Ali

Since Specialization
Citations

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

Fields of papers citing papers by Mumtaz Ali

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mumtaz Ali

This figure shows the co-authorship network connecting the top 25 collaborators of Mumtaz Ali. A scholar is included among the top collaborators of Mumtaz 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 Mumtaz Ali. Mumtaz 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.
Ali, Mumtaz, et al.. (2025). Improving daily reference evapotranspiration forecasts: Designing AI-enabled recurrent neural networks based long short-term memory. Ecological Informatics. 85. 102995–102995. 6 indexed citations
2.
Khosravi, Khabat, Sayed M. Bateni, Dongkyun Kim, et al.. (2025). Assessing Pan-Canada wildfire susceptibility by integrating satellite data with novel hybrid deep learning and black widow optimizer algorithms. The Science of The Total Environment. 977. 179369–179369. 3 indexed citations
4.
Ali, Mumtaz, et al.. (2024). Enhancing groundwater level prediction accuracy using interpolation techniques in deep learning models. Groundwater for Sustainable Development. 26. 101213–101213. 12 indexed citations
5.
Karbasi, Masoud, Mumtaz Ali, Aitazaz A. Farooque, et al.. (2024). Robust drought forecasting in Eastern Canada: Leveraging EMD-TVF and ensemble deep RVFL for SPEI index forecasting. Expert Systems with Applications. 256. 124900–124900. 12 indexed citations
6.
Kaur, A., et al.. (2024). Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review. IEEE Access. 12. 193902–193922. 1 indexed citations
7.
Jamei, Mehdi, Mumtaz Ali, Hassan Afzaal, et al.. (2023). Accurate monitoring of micronutrients in tilled potato soils of eastern Canada: Application of an eXplainable inspired-adaptive boosting framework coupled with SelectKbest. Computers and Electronics in Agriculture. 216. 108479–108479. 5 indexed citations
8.
Khan, Mohd Sajid, et al.. (2023). Non Decompressive Single Stage Bilateral Craniotomy in Traumatic Brain Injury. 17(1). 333–335. 1 indexed citations
9.
Hai, Tao, Sinan Q. Salih, Mustafa K. A. Mohammed, et al.. (2023). Development of high-resolution gridded data for water availability identification through GRACE data downscaling: Development of machine learning models. Atmospheric Research. 291. 106815–106815. 11 indexed citations
10.
Ibrahim, Hekmat, Zaher Mundher Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Miklas Scholz, et al.. (2023). Evaluation and Prediction of Groundwater Quality for Irrigation Using an Integrated Water Quality Indices, Machine Learning Models and GIS Approaches: A Representative Case Study. Water. 15(4). 694–694. 107 indexed citations breakdown →
12.
Ali, Mumtaz, et al.. (2021). Association of Cigarette Smoking with Dyslipidemia and Abdominal Obesity as Cardiovascular Risk Factors among Young Adults. SHILAP Revista de lepidopterología. 20(5). 341–344.
13.
Adarsh, S., et al.. (2021). Multifractal characterization and cross correlations of reference evapotranspiration time series of India. The European Physical Journal Special Topics. 230(21-22). 3845–3859. 8 indexed citations
15.
Yaseen‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, Zaher Mundher, Mohammed Suleman Aldlemy, Mumtaz Ali, et al.. (2020). State-of-the Art-Powerhouse, Dam Structure, and Turbine Operation and Vibrations. Sustainability. 12(4). 1676–1676. 24 indexed citations
16.
Ali, Mumtaz, Ravinesh C. Deo, Nathan Downs, & Tek Maraseni. (2018). Multi-stage hybridized online sequential extreme learning machine integrated with Markov Chain Monte Carlo copula-Bat algorithm for rainfall forecasting. Atmospheric Research. 213. 450–464. 62 indexed citations
17.
Ngân, Trần Thị, Mumtaz Ali, Dan E. Tamir, et al.. (2018). Logic connectives of complex fuzzy sets. 21(4). 344–357. 18 indexed citations
18.
Khan, Zahid, et al.. (2016). FREQUENCY AND CLINICAL PRESENTATION OF CEREBELLOPONTINE ANGLE TUMORS: AN EXPERIENCE IN DEPARTMENT OF NEUROSURGERY LADY READING HOSPITAL PESHAWAR. Journal of Postgraduate Medical Institute. 30(3). 1 indexed citations
19.
Ali, Mumtaz, et al.. (2016). SURGICAL OUTCOME OF SUPRATENTORIAL LOW GRADE GLIOMAS: STUDY OF 85 CASES. Journal of Postgraduate Medical Institute. 30(4).
20.
Shah, Rizwan, et al.. (2015). OUTCOME OF SURGICAL MANAGEMENT IN SPINAL MENINGIOMA: A STUDY OF 48 CASES. SHILAP Revista de lepidopterología. 3 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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