Padmavati Khandnor
- Cognitive Neuroscience top 10%
- Physiology
- Artificial Intelligence
- Signal Processing top 10%
- Cardiology and Cardiovascular Medicine
- Co-authors
- Trilok ChandAshima KhoslaTrilok Chand AseriNeelam GoelNeelesh KumarRajesh BhatiaSandeep HaritRohit Goyal
- Topics
- Energy Efficient Wireless Sensor Networks (9 papers)Mobile Ad Hoc Networks (6 papers)EEG and Brain-Computer Interfaces (6 papers)
- Journals
- Expert Systems with ApplicationsEngineering Applications of Artificial IntelligenceJournal of Neural Engineering
- Partner nations
- India
In The Last Decade
Padmavati Khandnor
26 papers receiving 428 citations
Peers
Comparison fields: 5 of 88
- Cognitive Neuroscience 204
- Physiology 74
- Artificial Intelligence 69
- Signal Processing 67
- Cardiology and Cardiovascular Medicine 64
Countries citing papers authored by Padmavati Khandnor
This map shows the geographic impact of Padmavati Khandnor'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 Padmavati Khandnor with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Padmavati Khandnor more than expected).
Fields of papers citing papers by Padmavati Khandnor
This network shows the impact of papers produced by Padmavati Khandnor. 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 Padmavati Khandnor. The network helps show where Padmavati Khandnor may publish in the future.
Co-authorship network of co-authors of Padmavati Khandnor
This figure shows the co-authorship network connecting the top 25 collaborators of Padmavati Khandnor. A scholar is included among the top collaborators of Padmavati Khandnor 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 Padmavati Khandnor. Padmavati Khandnor 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 | 3 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 4 | |
| 8 | 16 | |
| 9 | 31 | |
| 10 | 172 | |
| 11 | 8 | |
| 12 | 10 | |
| 13 | 9 | |
| 14 | 2 | |
| 15 | 5 | |
| 16 | 1 | |
| 17 | 4 | |
| 18 | 11 | |
| 19 | 3 | |
| 20 | 1 |
About Padmavati Khandnor
Padmavati Khandnor is a scholar working on General Dentistry, Computer Networks and Communications and Signal Processing, having authored 28 papers that have together received 444 indexed citations. Recurring topics across this work include Energy Efficient Wireless Sensor Networks (9 papers), Mobile Ad Hoc Networks (6 papers) and EEG and Brain-Computer Interfaces (6 papers). The work is most often cited by research in Cognitive Neuroscience (204 citations), Signal Processing (67 citations) and Experimental and Cognitive Psychology (57 citations). Padmavati Khandnor has collaborated with scholars based in India. Frequent co-authors include Trilok Chand, Ashima Khosla, Trilok Chand Aseri, Neelam Goel, Neelesh Kumar, Rajesh Bhatia, Sandeep Harit, Rohit Goyal, Megha Sharma and Ajay K. Sharma. Their work appears in journals such as Expert Systems with Applications, Engineering Applications of Artificial Intelligence and Journal of Neural Engineering.
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.