Maqbool Khan
Impact in
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- Digital Transformation in Industry
- Industrial Vision Systems and Defect Detection
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- IoT and Edge/Fog Computing
Papers in
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- Privacy-Preserving Technologies in Data 4
- Sentiment Analysis and Opinion Mining 4
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- IoT and Edge/Fog Computing 9
- Peer-to-Peer Network Technologies 4
- Co-authors
- Wanchun Dou (9 shared papers)Xiaolong Xu (6 shared papers)Xiaotong Wu (3 shared papers)Wajid Rafique (10 shared papers)Shui Yu (3 shared papers)Salabat Khan (4 shared papers)Nadeem Sarwar (4 shared papers)Xuyun Zhang (1 shared paper)
In The Last Decade
Maqbool Khan
50 papers receiving 793 citations
Peers
Comparison fields: 5 of 109
- Industrial and Manufacturing Engineering 117
- Computer Networks and Communications 195
- Information Systems 181
- Health Informatics 9
- Computer Science Applications 32
Countries citing papers authored by Maqbool Khan
This map shows the geographic impact of Maqbool 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 Maqbool Khan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maqbool Khan more than expected).
Fields of papers citing papers by Maqbool Khan
This network shows the impact of papers produced by Maqbool 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 Maqbool Khan. The network helps show where Maqbool Khan may publish in the future.
Co-authors
The 25 scholars most cited alongside Maqbool 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
Showing the 20 most-cited of 63 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 149 | |
| 2 | 2017 | 91 | |
| 3 | 2023 | 70 | |
| 4 | 2020 | 55 | |
| 5 | 2017 | 45 | |
| 6 | 2024 | 28 | |
| 7 | 2023 | 25 | |
| 8 | 2019 | 24 | |
| 9 | 2023 | 23 | |
| 10 | 2022 | 22 | |
| 11 | 2020 | 20 | |
| 12 | 2019 | 18 | |
| 13 | 2024 | 16 | |
| 14 | 2021 | 16 | |
| 15 | 2022 | 15 | |
| 16 | 2019 | 15 | |
| 17 | 2020 | 14 | |
| 18 | 2022 | 13 | |
| 19 | 2016 | 13 | |
| 20 | 2023 | 12 |
About Maqbool Khan
Maqbool Khan is a scholar working on Artificial Intelligence, Computer Networks and Communications, Information Systems, Computer Vision and Pattern Recognition and Industrial and Manufacturing Engineering, having authored 63 papers that have together received 821 indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (9 papers), Blockchain Technology Applications and Security (6 papers), Digital Transformation in Industry (5 papers), Vehicle License Plate Recognition (4 papers), Privacy-Preserving Technologies in Data (4 papers), Peer-to-Peer Network Technologies (4 papers), Sentiment Analysis and Opinion Mining (4 papers) and Complex Network Analysis Techniques (4 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (117 citations), Computer Networks and Communications (195 citations), Information Systems (181 citations), Health Informatics (9 citations) and Computer Science Applications (32 citations). Maqbool Khan has collaborated with scholars based in Pakistan, China and Austria. Frequent co-authors include Wanchun Dou, Xiaolong Xu, Xiaotong Wu, Wajid Rafique, Shui Yu, Salabat Khan, Nadeem Sarwar, Xuyun Zhang, Shengjun Xue and Sheikh Md. Abu Hena Mostafa Alim. Their work appears in journals such as IEEE Access, Computers, materials & continua/Computers, materials & continua (Print), Tsinghua Science & Technology, Nanoscale and ACM Transactions on Autonomous and Adaptive Systems.
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.