Raouf Khayami
- Computer Networks and Communications top 1%
- Signal Processing top 1%
- Artificial Intelligence top 2%
- Information Systems top 2%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Kim‐Kwang Raymond ChooAli DehghantanhaReza JavidanHamed HaddadPajouhHamid Reza BoveiriAlireza MehdizadehMohamed ElhosenyM. Gunasekaran
- Topics
- Network Security and Intrusion Detection (5 papers)Advanced Malware Detection Techniques (5 papers)Medical Image Segmentation Techniques (4 papers)
- Journals
- Future Generation Computer SystemsNeural Computing and ApplicationsBiomedical Signal Processing and Control
- Partner nations
- IranUnited StatesUnited Kingdom
In The Last Decade
Raouf Khayami
15 papers receiving 1.1k citations
Hit Papers
Peers
Comparison fields: 5 of 82
- Computer Networks and Communications 806
- Signal Processing 560
- Artificial Intelligence 498
- Information Systems 280
- Computer Vision and Pattern Recognition 144
Countries citing papers authored by Raouf Khayami
This map shows the geographic impact of Raouf Khayami'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 Raouf Khayami with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Raouf Khayami more than expected).
Fields of papers citing papers by Raouf Khayami
This network shows the impact of papers produced by Raouf Khayami. 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 Raouf Khayami. The network helps show where Raouf Khayami may publish in the future.
Co-authorship network of co-authors of Raouf Khayami
This figure shows the co-authorship network connecting the top 25 collaborators of Raouf Khayami. A scholar is included among the top collaborators of Raouf Khayami 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 Raouf Khayami. Raouf Khayami is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 1 | |
| 3 | 38 | |
| 4 | 9 | |
| 5 | 9 | |
| 6 | 53 | |
| 7 | 113 | |
| 8 | 99 | |
| 9 | A deep Recurrent Neural Network based approach for Internet of Things malware threat huntingbreakdown → | 296 |
| 10 | 97 | |
| 11 | 5 | |
| 12 | 37 | |
| 13 | A Two-Layer Dimension Reduction and Two-Tier Classification Model for Anomaly-Based Intrusion Detection in IoT Backbone Networksbreakdown → | 328 |
| 14 | 2 | |
| 15 | 16 |
About Raouf Khayami
Raouf Khayami is a scholar working on Signal Processing, Computer Networks and Communications and Neurology, having authored 15 papers that have together received 1.1k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (5 papers), Advanced Malware Detection Techniques (5 papers) and Medical Image Segmentation Techniques (4 papers). The work is most often cited by research in Signal Processing (560 citations), Computer Networks and Communications (806 citations) and Artificial Intelligence (498 citations). Raouf Khayami has collaborated with scholars based in Iran, United States and United Kingdom. Frequent co-authors include Kim‐Kwang Raymond Choo, Ali Dehghantanha, Reza Javidan, Hamed HaddadPajouh, Hamid Reza Boveiri, Alireza Mehdizadeh, Mohamed Elhoseny, M. Gunasekaran, Marzieh Ahmadzadeh and Sajad Homayoun. Their work appears in journals such as Future Generation Computer Systems, Neural Computing and Applications and Biomedical Signal Processing and Control.
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.