Faisal Asad
Impact in
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- Model Reduction and Neural Networks
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- Probabilistic and Robust Engineering Design
Papers in
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- Aerospace Engineering and Energy Systems 4
- Spacecraft and Cryogenic Technologies 2
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- Gas Dynamics and Kinetic Theory 6
- Co-authors
- Charbel Farhat (12 shared papers)Philip Avery (7 shared papers)Radek Tezaur (2 shared papers)Jason Rabinovitch (6 shared papers)Joan B. Soriano (1 shared paper)Mark Drela (1 shared paper)Devansh R. Agrawal (1 shared paper)R. John Hansman (1 shared paper)
- Journals
- Computer Methods in Applied Mechanics and Engineering (4 papers)AIAA Journal (2 papers)Respiratory Medicine (1 paper)International Journal for Numerical Methods in Engineering (1 paper)AIAA SCITECH 2023 Forum (1 paper)
- Partner nations
- United StatesPakistanSaudi Arabia
In The Last Decade
Faisal Asad
16 papers receiving 282 citations
Faisal Asad's Hit Papers
Peers
Comparison fields: 5 of 60
- Statistical and Nonlinear Physics 118
- Statistics, Probability and Uncertainty 45
- Mechanics of Materials 82
- Fluid Flow and Transfer Processes 18
- Computational Mechanics 46
Countries citing papers authored by Faisal Asad
This map shows the geographic impact of Faisal Asad'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 Faisal Asad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Faisal Asad more than expected).
Fields of papers citing papers by Faisal Asad
This network shows the impact of papers produced by Faisal Asad. 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 Faisal Asad. The network helps show where Faisal Asad may publish in the future.
Co-authors
The 11 scholars most cited alongside Faisal Asad, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | A mechanics‐informed artificial neural network approach in data‐driven constitutive modeling Hit paper breakdown → | 2022 | 143 |
| 2 | 2023 | 32 | |
| 3 | 2011 | 27 | |
| 4 | 2022 | 24 | |
| 5 | 2022 | 13 | |
| 6 | 2023 | 12 | |
| 7 | 2022 | 11 | |
| 8 | 2019 | 10 | |
| 9 | 2022 | 8 | |
| 10 | 2024 | 3 | |
| 11 | 2022 | 2 | |
| 12 | 2022 | 1 | |
| 13 | 2022 | 1 | |
| 14 | 2024 | 1 | |
| 15 | 2024 | 1 | |
| 16 | 2026 | 1 | |
| 17 | 2018 | 1 | |
| 18 | 2023 | 0 | |
| 19 | 2025 | 0 | |
| 20 | 2022 | 0 |
About Faisal Asad
Faisal Asad is a scholar working on Aerospace Engineering, Applied Mathematics, Statistical and Nonlinear Physics, Physiology and Mechanics of Materials, having authored 20 papers that have together received 291 indexed citations. Recurring topics across this work include Gas Dynamics and Kinetic Theory (6 papers), Obstructive Sleep Apnea Research (5 papers), Model Reduction and Neural Networks (5 papers), Aerospace Engineering and Energy Systems (4 papers), Composite Material Mechanics (4 papers), Elasticity and Material Modeling (3 papers), Probabilistic and Robust Engineering Design (2 papers) and Spacecraft and Cryogenic Technologies (2 papers). The work is most often cited by research in Statistical and Nonlinear Physics (118 citations), Statistics, Probability and Uncertainty (45 citations), Mechanics of Materials (82 citations), Fluid Flow and Transfer Processes (18 citations) and Computational Mechanics (46 citations). Faisal Asad has collaborated with scholars based in United States, Pakistan and Saudi Arabia. Frequent co-authors include Charbel Farhat, Philip Avery, Radek Tezaur, Jason Rabinovitch, Joan B. Soriano, Mark Drela, Devansh R. Agrawal, R. John Hansman, Saif Ur Rehman and Savio J. Poovathingal. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, AIAA Journal, Respiratory Medicine, International Journal for Numerical Methods in Engineering and AIAA SCITECH 2023 Forum.
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.