Salman Khan
- Molecular Biology
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Computational Theory and Mathematics top 5%
- Microbiology top 5%
- Co-authors
- Shahid AkbarMaqsood HayatFarman AliNadeem IqbalMukhtaj KhanAshfaq AhmadFahad Shahbaz KhanMuhammad Tahir
- Topics
- Machine Learning in Bioinformatics (21 papers)Genomics and Phylogenetic Studies (13 papers)RNA and protein synthesis mechanisms (9 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceScientific ReportsIEEE Access
- Partner nations
- PakistanSaudi ArabiaUnited States
In The Last Decade
Salman Khan
49 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 120
- Molecular Biology 566
- Artificial Intelligence 217
- Computer Vision and Pattern Recognition 167
- Computational Theory and Mathematics 128
- Microbiology 91
Countries citing papers authored by Salman Khan
This map shows the geographic impact of Salman 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 Salman Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Salman Khan more than expected).
Fields of papers citing papers by Salman Khan
This network shows the impact of papers produced by Salman 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 Salman Khan. The network helps show where Salman Khan may publish in the future.
Co-authorship network of co-authors of Salman Khan
This figure shows the co-authorship network connecting the top 25 collaborators of Salman Khan. A scholar is included among the top collaborators of Salman Khan 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 Salman Khan. Salman Khan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 7 | |
| 5 | 2 | |
| 6 | 13 | |
| 7 | 0 | |
| 8 | 24 | |
| 9 | 2 | |
| 10 | 1 | |
| 11 | 11 | |
| 12 | 3 | |
| 13 | 0 | |
| 14 | 23 | |
| 15 | 41 | |
| 16 | 6 | |
| 17 | 23 | |
| 18 | 31 | |
| 19 | 29 | |
| 20 | IoTEC: IoT based Efficient Clustering Protocol for Wireless Sensor Network | 6 |
About Salman Khan
Salman Khan is a scholar working on Microbiology, Computer Vision and Pattern Recognition and Health Information Management, having authored 56 papers that have together received 1.1k indexed citations. Recurring topics across this work include Machine Learning in Bioinformatics (21 papers), Genomics and Phylogenetic Studies (13 papers) and RNA and protein synthesis mechanisms (9 papers). The work is most often cited by research in Microbiology (91 citations), Health Information Management (58 citations) and Health Informatics (14 citations). Salman Khan has collaborated with scholars based in Pakistan, Saudi Arabia and United States. Frequent co-authors include Shahid Akbar, Maqsood Hayat, Farman Ali, Nadeem Iqbal, Mukhtaj Khan, Ashfaq Ahmad, Fahad Shahbaz Khan, Muhammad Tahir, Muzammal Naseer and Sarah Gul. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Scientific Reports and IEEE Access.
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.