Mohammad Abu Alsheikh
- Electrical and Electronic Engineering top 10%
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering top 10%
- Computer Networks and Communications top 5%
- Artificial Intelligence top 10%
- Co-authors
- Yonglong TianAntonio TorralbaDina KatabiTianhong LiHang ZhaoM. ZhaoDusit NiyatoHwee-Pink Tan
- Topics
- IoT and Edge/Fog Computing (3 papers)Energy Harvesting in Wireless Networks (2 papers)Indoor and Outdoor Localization Technologies (2 papers)
- Cited by
- Human-Computer InteractionComputer Vision and Pattern RecognitionComputer Networks and Communications
- Partner nations
- AustraliaSingaporeUnited States
In The Last Decade
Mohammad Abu Alsheikh
11 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Electrical and Electronic Engineering 491
- Computer Vision and Pattern Recognition 358
- Biomedical Engineering 310
- Computer Networks and Communications 308
- Artificial Intelligence 196
Countries citing papers authored by Mohammad Abu Alsheikh
This map shows the geographic impact of Mohammad Abu Alsheikh'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 Abu Alsheikh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Abu Alsheikh more than expected).
Fields of papers citing papers by Mohammad Abu Alsheikh
This network shows the impact of papers produced by Mohammad Abu Alsheikh. 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 Abu Alsheikh. The network helps show where Mohammad Abu Alsheikh may publish in the future.
Co-authorship network of co-authors of Mohammad Abu Alsheikh
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammad Abu Alsheikh. A scholar is included among the top collaborators of Mohammad Abu Alsheikh 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 Mohammad Abu Alsheikh. Mohammad Abu Alsheikh is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 6 | |
| 5 | 2 | |
| 6 | 283 | |
| 7 | Through-Wall Human Pose Estimation Using Radio Signalsbreakdown → | 447 |
| 8 | 195 | |
| 9 | 3 | |
| 10 | 53 | |
| 11 | Markov decision processes with applications in wireless sensor networks: A survey | 146 |
About Mohammad Abu Alsheikh
Mohammad Abu Alsheikh is a scholar working on Human-Computer Interaction, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 11 papers that have together received 1.1k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (3 papers), Energy Harvesting in Wireless Networks (2 papers) and Indoor and Outdoor Localization Technologies (2 papers). The work is most often cited by research in Human-Computer Interaction (167 citations), Computer Vision and Pattern Recognition (358 citations) and Computer Networks and Communications (308 citations). Mohammad Abu Alsheikh has collaborated with scholars based in Australia, Singapore and United States. Frequent co-authors include Yonglong Tian, Antonio Torralba, Dina Katabi, Tianhong Li, Hang Zhao, M. Zhao, Dusit Niyato, Hwee-Pink Tan, Shaowei Lin and Zhu Han. Their work appears in journals such as IEEE Access, IEEE Journal on Selected Areas in Communications and IEEE Communications Magazine.
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.