Quamar Niyaz
- Computer Networks and Communications top 1%
- Artificial Intelligence top 2%
- Signal Processing top 1%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Co-authors
- Weiqing SunAhmad Y. JavaidMansoor AlamSidike PahedingVijay DevabhaktuniSamantha SmithKhair Al ShamailehAhmad Maroof Karimi
- Topics
- Network Security and Intrusion Detection (15 papers)Advanced Malware Detection Techniques (11 papers)Internet Traffic Analysis and Secure E-voting (9 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
- Partner nations
- United StatesIndia
In The Last Decade
Quamar Niyaz
31 papers receiving 1.2k citations
Hit Papers
Peers
Comparison fields: 5 of 88
- Computer Networks and Communications 934
- Artificial Intelligence 824
- Signal Processing 542
- Information Systems 189
- Computer Vision and Pattern Recognition 114
Countries citing papers authored by Quamar Niyaz
This map shows the geographic impact of Quamar Niyaz'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 Quamar Niyaz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quamar Niyaz more than expected).
Fields of papers citing papers by Quamar Niyaz
This network shows the impact of papers produced by Quamar Niyaz. 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 Quamar Niyaz. The network helps show where Quamar Niyaz may publish in the future.
Co-authorship network of co-authors of Quamar Niyaz
This figure shows the co-authorship network connecting the top 25 collaborators of Quamar Niyaz. A scholar is included among the top collaborators of Quamar Niyaz 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 Quamar Niyaz. Quamar Niyaz 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 | 2 | |
| 6 | 20 | |
| 7 | 35 | |
| 8 | 5 | |
| 9 | 13 | |
| 10 | 17 | |
| 11 | 13 | |
| 12 | 15 | |
| 13 | 6 | |
| 14 | 38 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | 20 | |
| 18 | A Deep Learning Approach for Network Intrusion Detection System. | 32 |
| 19 | 6 | |
| 20 | 5 |
About Quamar Niyaz
Quamar Niyaz is a scholar working on Signal Processing, Computer Networks and Communications and Information Systems, having authored 35 papers that have together received 1.3k indexed citations. Recurring topics across this work include Network Security and Intrusion Detection (15 papers), Advanced Malware Detection Techniques (11 papers) and Internet Traffic Analysis and Secure E-voting (9 papers). The work is most often cited by research in Signal Processing (542 citations), Computer Networks and Communications (934 citations) and Artificial Intelligence (824 citations). Quamar Niyaz has collaborated with scholars based in United States and India. Frequent co-authors include Weiqing Sun, Ahmad Y. Javaid, Mansoor Alam, Sidike Paheding, Vijay Devabhaktuni, Samantha Smith, Khair Al Shamaileh, Ahmad Maroof Karimi, Xiaoli Yang and Paheding Sidike. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications 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.