Kavitha Chandra

507 citations
47 papers · 353 · h-index 9

Impact in

Papers in

Kavitha Chandra

36 papers receiving 333 citations

Peers

Kavitha Chandra
Comparison fields: 5 of 81
  • Computer Networks and Communications 157
  • Signal Processing 57
  • Management Science and Operations Research 47
  • Computer Vision and Pattern Recognition 69
  • Management Information Systems 23
Replace Andrzej Kasprzak with:
Andrzej Kasprzak Poland
Songqiao Han China
Cándido López-Garcı́a Spain
Vishal Krishna Singh India
Waleed Hilal Canada
Yuyu Yuan China
Y. Ding China
Ilkyeun Ra United States
Kavitha Chandra relative to Andrzej Kasprzak Poland Andrzej Kasprzak's profile →
Citations per field
00.5×4.8×
Andrzej Kasprzak · 1×
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 47 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201571
2 200356
3 199955
4 198930
5 200723
6 200616
7 199116
8 200613
9 20029
10
Non-Linear Time-Series Models of Ethernet Traffic
19988
11 20047
12 20046
13 19966
14 19935
15 19924
16 20253
17 20203
18 19952
19 20242
20 20241

About Kavitha Chandra

Kavitha Chandra is a scholar working on Electrical and Electronic Engineering, Computer Networks and Communications, Computer Vision and Pattern Recognition, Signal Processing and Biomedical Engineering, having authored 47 papers that have together received 353 indexed citations. Recurring topics across this work include Network Traffic and Congestion Control (9 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), Video Coding and Compression Technologies (4 papers), Advanced MIMO Systems Optimization (4 papers) and Advanced Queuing Theory Analysis (3 papers). The work is most often cited by research in Computer Networks and Communications (157 citations), Signal Processing (57 citations), Management Science and Operations Research (47 citations), Computer Vision and Pattern Recognition (69 citations) and Management Information Systems (23 citations). Kavitha Chandra has collaborated with scholars based in United States, Japan and Fiji. Frequent co-authors include Amy R. Reibman, Charles Thompson, Asil Oztekin, Yao Chen, Richard L. Webber, A.E. Eckberg, Vineet Mehta, Max Denis, Sa Liu and Karen Daniels. Their work appears in journals such as The Journal of the Acoustical Society of America, IEEE/ACM Transactions on Networking, Omega, IEEE Access and IEEE Transactions on Vehicular Technology.

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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