Muhammad Mohebujjaman

497 citations
23 papers · 310 indexed · h-index 8
Topics
Computational Fluid Dynamics and Aerodynamics (8 papers)Advanced Numerical Methods in Computational Mathematics (7 papers)Model Reduction and Neural Networks (6 papers)

In The Last Decade

Muhammad Mohebujjaman

18 papers receiving 294 citations

Peers

Muhammad Mohebujjaman
Comparison fields: 5 of 55
  • Computational Mechanics 204
  • Statistical and Nonlinear Physics 143
  • Statistics, Probability and Uncertainty 65
  • Numerical Analysis 41
  • Biomedical Engineering 33
Replace Xuping Xie with:
Xuping Xie United States
Vincenzo Citro Italy
Jaume Peraire United States
Roland Griesse Austria
Guangming Yao United States
Gonzalo Rubio Spain
Christophe Audouze Canada
Irina Kalashnikova United States
Reza Pourgholi Iran
Murtazo Nazarov Sweden
Muhammad Mohebujjaman relative to Xuping Xie United States Xuping Xie's profile →
Citations per field
00.5×3.7×
Xuping Xie · 1×
Citations per year

Countries citing papers authored by Muhammad Mohebujjaman

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Mohebujjaman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Mohebujjaman

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Mohebujjaman. A scholar is included among the top collaborators of Muhammad Mohebujjaman 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 Muhammad Mohebujjaman. Muhammad Mohebujjaman 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
#WorkIndexed citations
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5 28
6 2
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12 2
13 24
14 20
15 97
16 0
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NUMERICAL ANALYSIS AND TESTING OF A FULLY DISCRETE, DECOUPLED PENALTY-PROJECTION ALGORITHM FOR MHD IN ELSASSER VARIABLE
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18 37
19 22
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About Muhammad Mohebujjaman

Muhammad Mohebujjaman is a scholar working on Computational Mechanics, Statistics, Probability and Uncertainty and Statistical and Nonlinear Physics, having authored 23 papers that have together received 310 indexed citations. Recurring topics across this work include Computational Fluid Dynamics and Aerodynamics (8 papers), Advanced Numerical Methods in Computational Mathematics (7 papers) and Model Reduction and Neural Networks (6 papers). The work is most often cited by research in Statistical and Nonlinear Physics (143 citations), Computational Mechanics (204 citations) and Statistics, Probability and Uncertainty (65 citations). Muhammad Mohebujjaman has collaborated with scholars based in United States, Bangladesh and Canada. Frequent co-authors include Leo G. Rebholz, Traian Iliescu, Xuping Xie, Md. Kamrujjaman, Md. Mamun Molla, Suvash C. Saha, Cătălin Trenchea, Nan Jiang, Md. Shahidul Islam and Md Mizanur Rahman. Their work appears in journals such as Journal of Computational Physics, Computer Methods in Applied Mechanics and Engineering and Energies.

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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