M. Ijaz Khan
- Computational Mechanics top 0.01%
- Fluid Dynamics and Turbulent Flows 292
- Heat and Mass Transfer in Porous Media 23
- Lattice Boltzmann Simulation Studies 14
- Biomedical Engineering top 0.01%
- Nanofluid Flow and Heat Transfer 478
- Mechanical Engineering top 0.01%
- Heat Transfer Mechanisms 342
- Heat Transfer and Optimization 135
- Fluid Flow and Transfer Processes top 0.2%
- Rheology and Fluid Dynamics Studies 50
- Modeling and Simulation top 0.2%
- Fractional Differential Equations Solutions 23
- Co-authors
- Tasawar HayatM. WaqasA. AlsaediAhmed AlsaediMuhammad Imran KhanSumaira QayyumFaris AlzahraniYu‐Ming Chu
- Journals
- Renewable and Sustainable Energy Reviews (1 paper)PLoS ONE (1 paper)Scientific Reports (8 papers)
- Partner nations
- PakistanSaudi ArabiaChina
In The Last Decade
M. Ijaz Khan
530 papers receiving 24.6k citations
Hit Papers
Peers
Comparison fields: 5 of 155
- Computational Mechanics 16.6k
- Biomedical Engineering 23.3k
- Mechanical Engineering 18.9k
- Fluid Flow and Transfer Processes 1.8k
- Modeling and Simulation 827
Countries citing papers authored by M. Ijaz Khan
This map shows the geographic impact of M. Ijaz Khan'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 M. Ijaz Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites M. Ijaz Khan more than expected).
Fields of papers citing papers by M. Ijaz Khan
This network shows the impact of papers produced by M. Ijaz Khan. 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 M. Ijaz Khan. The network helps show where M. Ijaz Khan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside M. Ijaz Khan, 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 | 2025 | 0 | |
| 2 | 2024 | 7 | |
| 3 | 2024 | 7 | |
| 4 | 2024 | 0 | |
| 5 | 2024 | 5 | |
| 6 | 2024 | 26 | |
| 7 | 2024 | 0 | |
| 8 | 2024 | 2 | |
| 9 | 2024 | 11 | |
| 10 | 2024 | 1 | |
| 11 | 2023 | 15 | |
| 12 | 2023 | 3 | |
| 13 | 2023 | 6 | |
| 14 | 2023 | 9 | |
| 15 | 2022 | 44 | |
| 16 | 2022 | 28 | |
| 17 | Heat Transport Exploration for Hybrid Nanoparticle (Cu, Fe3O4)—Based Blood Flow via Tapered Complex Wavy Curved Channel with Slip Featuresbreakdown → | 2022 | 151 |
| 18 | 2021 | 42 | |
| 19 | 2019 | 26 | |
| 20 | 2019 | 12 |
About M. Ijaz Khan
M. Ijaz Khan is a scholar working on Computational Mechanics, Biomedical Engineering and Mechanical Engineering, having authored 538 papers that have together received 25.3k indexed citations. Recurring topics across this work include Nanofluid Flow and Heat Transfer (478 papers), Heat Transfer Mechanisms (342 papers), Fluid Dynamics and Turbulent Flows (292 papers), Heat Transfer and Optimization (135 papers), Rheology and Fluid Dynamics Studies (50 papers), Fractional Differential Equations Solutions (23 papers), Heat and Mass Transfer in Porous Media (23 papers) and Lattice Boltzmann Simulation Studies (14 papers). The work is most often cited by research in Computational Mechanics (16.6k citations), Biomedical Engineering (23.3k citations) and Mechanical Engineering (18.9k citations). M. Ijaz Khan has collaborated with scholars based in Pakistan, Saudi Arabia and China. Frequent co-authors include Tasawar Hayat, M. Waqas, A. Alsaedi, Ahmed Alsaedi, Muhammad Imran Khan, Sumaira Qayyum, Faris Alzahrani, Yu‐Ming Chu, Sami Ullah Khan and Seifedine Kadry. Their work appears in journals such as Renewable and Sustainable Energy Reviews, PLoS ONE and Scientific Reports.
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.