S. Arunkumar
Impact in
- Bioengineering top 5%
- Analytical Chemistry and Sensors
- Hardware and Architecture top 10%
Papers in
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- Analytical Chemistry and Sensors 2
-
- Scheduling and Optimization Algorithms 2
- Co-authors
- Sunkara V. ManoramaMatthew HennessyP. ManjulaSu Han ParkSeunghun JungYoung‐Bae KimD.-W. LeeChandran Balamurugan
- Journals
- Sensors and Actuators B Chemical (3 papers)Decision Support Systems (1 paper)IEEE Antennas and Wireless Propagation Letters (1 paper)Parallel Computing (1 paper)Acta Informatica (1 paper)
- Partner nations
- IndiaSouth KoreaIraq
In The Last Decade
S. Arunkumar
13 papers receiving 335 citations
Peers
Comparison fields: 5 of 47
- Bioengineering 90
- Hardware and Architecture 29
- Electrical and Electronic Engineering 204
- Computational Theory and Mathematics 46
- Computer Networks and Communications 61
Countries citing papers authored by S. Arunkumar
This map shows the geographic impact of S. Arunkumar'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 S. Arunkumar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Arunkumar more than expected).
Fields of papers citing papers by S. Arunkumar
This network shows the impact of papers produced by S. Arunkumar. 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 S. Arunkumar. The network helps show where S. Arunkumar may publish in the future.
Co-authorship network
The 17 scholars most cited alongside S. Arunkumar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 2 | |
| 3 | A Machine Learning Approach to Analyze and Predict the Severity of Road Accidents | 2021 | 3 |
| 4 | 2018 | 3 | |
| 5 | 2016 | 39 | |
| 6 | 2016 | 93 | |
| 7 | IMPLEMENTATION OF LEAST MEAN SQUARE ALGORITHM FOR SINUSOIDAL AND AUDIO DENOISING USING FPGA | 2013 | 1 |
| 8 | 2012 | 9 | |
| 9 | 2012 | 12 | |
| 10 | 2010 | 1 | |
| 11 | 2010 | 82 | |
| 12 | 2005 | 0 | |
| 13 | 1995 | 23 | |
| 14 | 1992 | 23 | |
| 15 | 1992 | 54 | |
| 16 | 1991 | 5 |
About S. Arunkumar
S. Arunkumar is a scholar working on Bioengineering, Industrial and Manufacturing Engineering, Signal Processing, Computer Networks and Communications and Electrical and Electronic Engineering, having authored 16 papers that have together received 350 indexed citations. Recurring topics across this work include Gas Sensing Nanomaterials and Sensors (4 papers), ZnO doping and properties (3 papers), VLSI and FPGA Design Techniques (2 papers), Advanced Adaptive Filtering Techniques (2 papers), Advanced Chemical Sensor Technologies (2 papers), Scheduling and Optimization Algorithms (2 papers), Analytical Chemistry and Sensors (2 papers) and Power Line Communications and Noise (1 paper). The work is most often cited by research in Bioengineering (90 citations), Hardware and Architecture (29 citations), Electrical and Electronic Engineering (204 citations), Computational Theory and Mathematics (46 citations) and Computer Networks and Communications (61 citations). S. Arunkumar has collaborated with scholars based in India, South Korea and Iraq. Frequent co-authors include Sunkara V. Manorama, Matthew Hennessy, P. Manjula, Su Han Park, Seunghun Jung, Young‐Bae Kim, D.-W. Lee, Chandran Balamurugan, Dong‐Weon Lee and Tian Hou. Their work appears in journals such as Sensors and Actuators B Chemical, Decision Support Systems, IEEE Antennas and Wireless Propagation Letters, Parallel Computing and Acta Informatica.
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.