Mohammad Khalil

41 papers receiving 465 citations

Peers

Mohammad Khalil
Comparison fields: 5 of 62
  • Statistics, Probability and Uncertainty 185
  • Fluid Flow and Transfer Processes 62
  • Computational Mechanics 131
  • Statistical and Nonlinear Physics 75
  • Environmental Engineering 77
Replace Zhenghong Gao with:
Zhenghong Gao China
Paul G. A. Cizmas United States
Pietro Marco Congedo France
José Camberos United States
David J. J. Toal United Kingdom
Utz Wever Germany
Rohit Tripathy United States
David J. Knezevic United States
Marc Montagnac France
Anthony Nouy France
Mohammad Khalil relative to Zhenghong Gao China Zhenghong Gao's profile →
Citations per field
00.5×6.9×
Zhenghong Gao · 1×
Citations per year

Countries citing papers authored by Mohammad Khalil

Since Specialization
Citations

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

Fields of papers citing papers by Mohammad Khalil

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mohammad Khalil, 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 Mohammad Khalil Line = papers co-authored together Mohammad Khalil links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 45 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201439
2 200835
3 200735
4 201234
5 201734
6 201532
7 201421
8 201319
9 201819
10 201519
11 202018
12 201817
13 201616
14 201716
15 201614
16 200914
17 201910
18 20168
19 20177
20 20207

About Mohammad Khalil

Mohammad Khalil is a scholar working on Statistics, Probability and Uncertainty, Artificial Intelligence, Computational Mechanics, Environmental Engineering and Civil and Structural Engineering, having authored 45 papers that have together received 472 indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (23 papers), Wind and Air Flow Studies (10 papers), Structural Health Monitoring Techniques (8 papers), Target Tracking and Data Fusion in Sensor Networks (7 papers), Gaussian Processes and Bayesian Inference (6 papers), Control Systems and Identification (5 papers), Advanced Combustion Engine Technologies (5 papers) and Combustion and flame dynamics (5 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (185 citations), Fluid Flow and Transfer Processes (62 citations), Computational Mechanics (131 citations), Statistical and Nonlinear Physics (75 citations) and Environmental Engineering (77 citations). Mohammad Khalil has collaborated with scholars based in United States, Canada and United Kingdom. Frequent co-authors include Abhijit Sarkar, Dominique Poirel, Sondipon Adhikari, Habib N. Najm, Guilhem Lacaze, Joseph Oefelein, Chris L. Pettit, Cosmin Safta, H.A. Farag and Mohamed A. Abdou. Their work appears in journals such as Journal of Sound and Vibration, Computer Methods in Applied Mechanics and Engineering, Proceedings of the Combustion Institute, Combustion Theory and Modelling and Journal of Computational Physics.

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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