Moin‐ud‐Din Junjua

402 citations
40 papers · 287 · h-index 10

Impact in

Papers in

Moin‐ud‐Din Junjua

36 papers receiving 276 citations

Peers

Moin‐ud‐Din Junjua
Comparison fields: 5 of 48
  • Modeling and Simulation 74
  • Numerical Analysis 78
  • Statistical and Nonlinear Physics 74
  • Applied Mathematics 43
  • Computational Mechanics 42
Replace Farooq Ahmed Shah with:
Farooq Ahmed Shah Pakistan
Monairah Alansari Saudi Arabia
Sajid Iqbal Pakistan
Ashish Awasthi India
Hafedh Rguigui Tunisia
Baoli Yin China
Zhi-Wei Fang Macao
Reza Mohammadi Iran
Xiuling Hu China
Barbara Zwicknagl Germany
Moin‐ud‐Din Junjua relative to Farooq Ahmed Shah Pakistan Farooq Ahmed Shah's profile →
Citations per field
00.5×4.4×
Farooq Ahmed Shah · 1×
Citations per year

Countries citing papers authored by Moin‐ud‐Din Junjua

Since Specialization
Citations

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

Fields of papers citing papers by Moin‐ud‐Din Junjua

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Moin‐ud‐Din Junjua. 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 Moin‐ud‐Din Junjua. The network helps show where Moin‐ud‐Din Junjua may publish in the future.

Co-authors

The 25 scholars most cited alongside Moin‐ud‐Din Junjua, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Moin‐ud‐Din Junjua Line = papers co-authored together Moin‐ud‐Din Junjua links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 40 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202054
2 201932
3 202420
4 202415
5 201511
6 202110
7 202410
8 201510
9 201810
10 20249
11 20247
12 20247
13 20247
14 20246
15 20196
16 20236
17 20246
18 20246
19 20256
20 20245

About Moin‐ud‐Din Junjua

Moin‐ud‐Din Junjua is a scholar working on Numerical Analysis, Biomedical Engineering, Computational Mechanics, Modeling and Simulation and Statistical and Nonlinear Physics, having authored 40 papers that have together received 287 indexed citations. Recurring topics across this work include Iterative Methods for Nonlinear Equations (14 papers), Nanofluid Flow and Heat Transfer (12 papers), Advanced Optimization Algorithms Research (12 papers), Fractional Differential Equations Solutions (11 papers), Matrix Theory and Algorithms (10 papers), Nonlinear Waves and Solitons (9 papers), Nonlinear Photonic Systems (7 papers) and Fluid Dynamics and Turbulent Flows (5 papers). The work is most often cited by research in Modeling and Simulation (74 citations), Numerical Analysis (78 citations), Statistical and Nonlinear Physics (74 citations), Applied Mathematics (43 citations) and Computational Mechanics (42 citations). Moin‐ud‐Din Junjua has collaborated with scholars based in Pakistan, China and Saudi Arabia. Frequent co-authors include Saima Akram, Sarfaraz Ahmed, Abdul Ghaffar, Dumitru Bǎleanu, Shabbir Ahmad, Ahmed S. Hendy, Kottakkaran Sooppy Nisar, Gullnaz Shahzadi, Humaira Kalsoom and Sabir Hussain. Their work appears in journals such as Nanotechnology Reviews, Scientific Reports, International Journal of Computational Methods, PLoS ONE and Revista de la Real Academia de Ciencias Exactas Físicas y Naturales Serie A Matemáticas.

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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