Sameena Naaz
- Artificial Intelligence
- Information Systems top 10%
- Computer Networks and Communications top 10%
- Signal Processing
- Electrical and Electronic Engineering
- Co-authors
- Farheen SiddiquiOzair AlamShahab Saquib SohailM. Afshar AlamLamya Ahmed Al‐KeridisSyed Amir AshrafParul AgarwalVrinda Sharma
- Topics
- Artificial Intelligence in Healthcare (6 papers)Cloud Computing and Resource Management (5 papers)IoT and Edge/Fog Computing (4 papers)
- Journals
- Journal of EthnopharmacologyInternational Journal of Environmental Research and Public HealthSymmetry
- Partner nations
- IndiaUnited KingdomSaudi Arabia
In The Last Decade
Sameena Naaz
32 papers receiving 231 citations
Peers
Comparison fields: 5 of 84
- Artificial Intelligence 90
- Information Systems 75
- Computer Networks and Communications 62
- Signal Processing 40
- Electrical and Electronic Engineering 29
Countries citing papers authored by Sameena Naaz
This map shows the geographic impact of Sameena Naaz'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 Sameena Naaz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sameena Naaz more than expected).
Fields of papers citing papers by Sameena Naaz
This network shows the impact of papers produced by Sameena Naaz. 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 Sameena Naaz. The network helps show where Sameena Naaz may publish in the future.
Co-authorship network of co-authors of Sameena Naaz
This figure shows the co-authorship network connecting the top 25 collaborators of Sameena Naaz. A scholar is included among the top collaborators of Sameena Naaz 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 Sameena Naaz. Sameena Naaz 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 | 2 | |
| 3 | 5 | |
| 4 | 4 | |
| 5 | 1 | |
| 6 | 13 | |
| 7 | 29 | |
| 8 | 5 | |
| 9 | 2 | |
| 10 | 0 | |
| 11 | 1 | |
| 12 | 18 | |
| 13 | 8 | |
| 14 | 1 | |
| 15 | 2 | |
| 16 | 2 | |
| 17 | 5 | |
| 18 | 3 | |
| 19 | 2 | |
| 20 | 1 |
About Sameena Naaz
Sameena Naaz is a scholar working on Health Information Management, Signal Processing and Information Systems, having authored 37 papers that have together received 246 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (6 papers), Cloud Computing and Resource Management (5 papers) and IoT and Edge/Fog Computing (4 papers). The work is most often cited by research in Signal Processing (40 citations), Information Systems (75 citations) and Artificial Intelligence (90 citations). Sameena Naaz has collaborated with scholars based in India, United Kingdom and Saudi Arabia. Frequent co-authors include Farheen Siddiqui, Ozair Alam, Shahab Saquib Sohail, M. Afshar Alam, Lamya Ahmed Al‐Keridis, Syed Amir Ashraf, Parul Agarwal, Vrinda Sharma, Dag Øivind Madsen and Mohd Adnan. Their work appears in journals such as Journal of Ethnopharmacology, International Journal of Environmental Research and Public Health and Symmetry.
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.