Naina Chaudhary
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Computer Networks and Communications
- Information Systems
- Plant Science
- Co-authors
- Gurinder SinghDanish AtherRajneesh KlerGarima BhardwajS. Vikram SinghKulbir SinghBalvinder ShuklaVinita Sharma
- Topics
- Artificial Intelligence in Healthcare (3 papers)Building Energy and Comfort Optimization (2 papers)Online Learning and Analytics (2 papers)
- Cited by
- Business and International ManagementSignal ProcessingComputer Vision and Pattern Recognition
- Journals
- AIP conference proceedings
- Partner nations
- IndiaUnited Arab EmiratesUzbekistan
In The Last Decade
Naina Chaudhary
18 papers receiving 201 citations
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 34
- Computer Vision and Pattern Recognition 27
- Computer Networks and Communications 27
- Information Systems 22
- Plant Science 20
Countries citing papers authored by Naina Chaudhary
This map shows the geographic impact of Naina Chaudhary'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 Naina Chaudhary with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naina Chaudhary more than expected).
Fields of papers citing papers by Naina Chaudhary
This network shows the impact of papers produced by Naina Chaudhary. 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 Naina Chaudhary. The network helps show where Naina Chaudhary may publish in the future.
Co-authorship network of co-authors of Naina Chaudhary
This figure shows the co-authorship network connecting the top 25 collaborators of Naina Chaudhary. A scholar is included among the top collaborators of Naina Chaudhary 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 Naina Chaudhary. Naina Chaudhary is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 0 | |
| 9 | 0 | |
| 10 | 0 | |
| 11 | 2 | |
| 12 | 0 | |
| 13 | 0 | |
| 14 | 0 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 2 | |
| 18 | 45 | |
| 19 | 38 | |
| 20 | 11 |
About Naina Chaudhary
Naina Chaudhary is a scholar working on Health Information Management, Business and International Management and Computer Science Applications, having authored 33 papers that have together received 232 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare (3 papers), Building Energy and Comfort Optimization (2 papers) and Online Learning and Analytics (2 papers). The work is most often cited by research in Business and International Management (5 citations), Signal Processing (15 citations) and Computer Vision and Pattern Recognition (27 citations). Naina Chaudhary has collaborated with scholars based in India, United Arab Emirates and Uzbekistan. Frequent co-authors include Gurinder Singh, Danish Ather, Rajneesh Kler, Garima Bhardwaj, S. Vikram Singh, Kulbir Singh, Balvinder Shukla, Vinita Sharma, K.D. Do and Reena Jain. Their work appears in journals such as AIP conference proceedings.
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.