Kavitha Chandra

507 citations
46 papers · 335 · h-index 9

Impact in

Papers in

Kavitha Chandra

35 papers receiving 317 citations

Peers

Kavitha Chandra
Comparison fields: 5 of 81
  • Computer Networks and Communications 145
  • Signal Processing 51
  • Management Science and Operations Research 47
  • Computer Vision and Pattern Recognition 62
  • Management Information Systems 22
Replace Monika Mangla with:
Monika Mangla India
Waleed Hilal Canada
Parus Khuwaja Pakistan
Nisarg Patel India
Y. Ding China
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Sudhakar Kumar India
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Kavitha Chandra relative to Monika Mangla India Monika Mangla's profile →
Citations per field
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Citations per year

Countries citing papers authored by Kavitha Chandra

Since Specialization
Citations

This map shows the geographic impact of Kavitha Chandra'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 Kavitha Chandra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kavitha Chandra more than expected).

Fields of papers citing papers by Kavitha Chandra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kavitha Chandra. 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 Kavitha Chandra. The network helps show where Kavitha Chandra may publish in the future.

Co-authors

The 25 scholars most cited alongside Kavitha Chandra, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Kavitha Chandra Line = papers co-authored together Kavitha Chandra links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 46 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201571
2 199953
3 200352
4 198930
5 200722
6 200615
7 199114
8 200613
9 20029
10
Non-Linear Time-Series Models of Ethernet Traffic
19988
11 20047
12 19935
13 20045
14 19924
15 20203
16 20252
17 19952
18 20242
19 20241
20
Asymptotic Solutions and Probabilistic Characterization for Ultrasonic Scattering in Biological Media
19921

About Kavitha Chandra

Kavitha Chandra is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition, Biomedical Engineering and Signal Processing, having authored 46 papers that have together received 335 indexed citations. Recurring topics across this work include Network Traffic and Congestion Control (8 papers), Wireless Communication Networks Research (6 papers), Advanced Wireless Network Optimization (6 papers), Image and Video Quality Assessment (5 papers), Acoustic Wave Phenomena Research (5 papers), Advanced MIMO Systems Optimization (4 papers), Advanced Queuing Theory Analysis (3 papers) and Video Coding and Compression Technologies (3 papers). The work is most often cited by research in Computer Networks and Communications (145 citations), Signal Processing (51 citations), Management Science and Operations Research (47 citations), Computer Vision and Pattern Recognition (62 citations) and Management Information Systems (22 citations). Kavitha Chandra has collaborated with scholars based in United States, Japan and Fiji. Frequent co-authors include Amy R. Reibman, Charles Thompson, Yao Chen, Asil Oztekin, Richard L. Webber, A.E. Eckberg, Vineet Mehta, Sa Liu, Karen Daniels and Max Denis. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE Transactions on Vehicular Technology, Proceedings of the IEEE, IEEE/ACM Transactions on Networking 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.

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