Vikram Jain

28 papers receiving 362 citations

Peers

Vikram Jain
Comparison fields: 5 of 42
  • Hardware and Architecture 92
  • Computer Vision and Pattern Recognition 104
  • Electrical and Electronic Engineering 235
  • Computer Networks and Communications 86
  • Computational Mathematics 2
Replace Jon J. Pimentel with:
Jon J. Pimentel United States
Linyan Mei Belgium
Sehwan Lee South Korea
Guy Boudoukh Israel
Junzhong Shen China
Andrew C. Ling Canada
Mostafa E. Salehi Iran
Davor Capalija Canada
Michael J. Klaiber Germany
Vikram Jain relative to Jon J. Pimentel United States Jon J. Pimentel's profile →
Citations per field
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Jon J. Pimentel · 1×
Citations per year

Countries citing papers authored by Vikram Jain

Since Specialization
Citations

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

Fields of papers citing papers by Vikram Jain

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Vikram Jain, 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 Vikram Jain Line = papers co-authored together Vikram Jain links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202197
2 202265
3 202246
4 202332
5 202430
6 202222
7
Survey on Recent Clustering Algorithms in Wireless Sensor Networks
201313
8 202112
9 20117
10 20217
11 20196
12 20074
13 20174
14 20193
15 20113
16 20233
17 20243
18 20243
19 20232
20 20252

About Vikram Jain

Vikram Jain is a scholar working on Hardware and Architecture, Computer Networks and Communications, Electrical and Electronic Engineering, Media Technology and Computer Vision and Pattern Recognition, having authored 31 papers that have together received 375 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (11 papers), CCD and CMOS Imaging Sensors (8 papers), Parallel Computing and Optimization Techniques (6 papers), Advanced Neural Network Applications (5 papers), Mobile Ad Hoc Networks (5 papers), Ferroelectric and Negative Capacitance Devices (4 papers), Energy Efficient Wireless Sensor Networks (3 papers) and Image Processing Techniques and Applications (3 papers). The work is most often cited by research in Hardware and Architecture (92 citations), Computer Vision and Pattern Recognition (104 citations), Electrical and Electronic Engineering (235 citations), Computer Networks and Communications (86 citations) and Computational Mathematics (2 citations). Vikram Jain has collaborated with scholars based in Belgium, United States and India. Frequent co-authors include Marian Verhelst, Juan Sebastian Piedrahita Giraldo, Linyan Mei, Pouya Houshmand, Debjyoti Bhattacharjee, Ioannis A. Papistas, Qilin Zheng, Diederik Verkest, Peter Debacker and Arindam Mallik. Their work appears in journals such as IEEE Journal of Solid-State Circuits, IEEE Transactions on Circuits and Systems I Regular Papers, IEEE Transactions on Computers, IEEE Transactions on Very Large Scale Integration (VLSI) Systems and Lecture notes in computer science.

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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