Mohammed Al‐Habib
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Signal Processing top 5%
- Sociology and Political Science
- Organizational Behavior and Human Resource Management top 10%
- Co-authors
- Kamal Al‐SabahiMajjed Al-QatfLasheng YuJamal Al‐KhatibChristopher J. RobertsonAvinash MalsheJoseph F. HairRobert C. Erffmeyer
- Topics
- Customer Service Quality and Loyalty (3 papers)Cutaneous Melanoma Detection and Management (3 papers)Anomaly Detection Techniques and Applications (3 papers)
- Partner nations
- ChinaSaudi ArabiaUnited States
In The Last Decade
Mohammed Al‐Habib
17 papers receiving 599 citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Artificial Intelligence 316
- Computer Networks and Communications 312
- Signal Processing 171
- Sociology and Political Science 111
- Organizational Behavior and Human Resource Management 82
Countries citing papers authored by Mohammed Al‐Habib
This map shows the geographic impact of Mohammed Al‐Habib'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 Mohammed Al‐Habib with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammed Al‐Habib more than expected).
Fields of papers citing papers by Mohammed Al‐Habib
This network shows the impact of papers produced by Mohammed Al‐Habib. 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 Mohammed Al‐Habib. The network helps show where Mohammed Al‐Habib may publish in the future.
Co-authorship network of co-authors of Mohammed Al‐Habib
This figure shows the co-authorship network connecting the top 25 collaborators of Mohammed Al‐Habib. A scholar is included among the top collaborators of Mohammed Al‐Habib 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 Mohammed Al‐Habib. Mohammed Al‐Habib is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 8 | |
| 9 | 5 | |
| 10 | 2 | |
| 11 | Deep Learning Approach Combining Sparse Autoencoder With SVM for Network Intrusion Detectionbreakdown → | 364 |
| 12 | 30 | |
| 13 | 20 | |
| 14 | 4 | |
| 15 | 7 | |
| 16 | 10 | |
| 17 | 2 | |
| 18 | 19 | |
| 19 | 86 | |
| 20 | 1 |
About Mohammed Al‐Habib
Mohammed Al‐Habib is a scholar working on General Decision Sciences, Applied Microbiology and Biotechnology and Organizational Behavior and Human Resource Management, having authored 23 papers that have together received 648 indexed citations. Recurring topics across this work include Customer Service Quality and Loyalty (3 papers), Cutaneous Melanoma Detection and Management (3 papers) and Anomaly Detection Techniques and Applications (3 papers). The work is most often cited by research in Signal Processing (171 citations), Computer Networks and Communications (312 citations) and Artificial Intelligence (316 citations). Mohammed Al‐Habib has collaborated with scholars based in China, Saudi Arabia and United States. Frequent co-authors include Kamal Al‐Sabahi, Majjed Al-Qatf, Lasheng Yu, Jamal Al‐Khatib, Christopher J. Robertson, Avinash Malshe, Joseph F. Hair, Robert C. Erffmeyer, Scott B. Friend and Xingfu Wang. Their work appears in journals such as Journal of Business Research, IEEE Access and Neural Networks.
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.