M. Sasikumar

947 citations
50 papers · 694 · h-index 17

Impact in

Papers in

M. Sasikumar

45 papers receiving 657 citations

Peers

M. Sasikumar
Comparison fields: 5 of 79
  • Automotive Engineering 100
  • Computer Vision and Pattern Recognition 146
  • Polymers and Plastics 94
  • Renewable Energy, Sustainability and the Environment 103
  • Electronic, Optical and Magnetic Materials 115
Replace Jingyi Qu with:
Jingyi Qu China
Zehao Zhu China
Guan-Cheng Chen Taiwan
Shuaijie Li China
Gaofeng Li China
Velmathi Guruviah India
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Citations per field
00.5×4.7×
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Citations per year

Countries citing papers authored by M. Sasikumar

Since Specialization
Citations

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

Fields of papers citing papers by M. Sasikumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200868
2 201858
3
Simple Syntactic and Morphological Processing Can Help English-Hindi Statistical Machine Translation.
200856
4 201836
5 202135
6 201833
7
Survey of Medical Image Watermarking Algorithms
200730
8 202127
9 201926
10 202126
11 202023
12 201823
13 202120
14 202219
15 202119
16 201918
17 202317
18 202313
19 202413
20 202413

About M. Sasikumar

M. Sasikumar is a scholar working on Electrical and Electronic Engineering, Materials Chemistry, Renewable Energy, Sustainability and the Environment, Electronic, Optical and Magnetic Materials and Biomedical Engineering, having authored 50 papers that have together received 694 indexed citations. Recurring topics across this work include Advanced Battery Materials and Technologies (8 papers), Supercapacitor Materials and Fabrication (8 papers), Advancements in Battery Materials (7 papers), Advanced Battery Technologies Research (6 papers), Advanced battery technologies research (6 papers), Conducting polymers and applications (5 papers), Electrocatalysts for Energy Conversion (5 papers) and Nanoparticles: synthesis and applications (4 papers). The work is most often cited by research in Automotive Engineering (100 citations), Computer Vision and Pattern Recognition (146 citations), Polymers and Plastics (94 citations), Renewable Energy, Sustainability and the Environment (103 citations) and Electronic, Optical and Magnetic Materials (115 citations). M. Sasikumar has collaborated with scholars based in India, South Korea and Chile. Frequent co-authors include R. Hari Krishna, P. Sivakumar, M. Raja, Ritesh Shah, Pushpak Bhattacharyya, A. Sakunthala, Helen Annal Therese, S. Rajendran, Elaiyappillai Elanthamilan and Arulappan Durairaj. Their work appears in journals such as Applied Surface Science Advances, Journal of Materials Science Materials in Electronics, Ionics, Materials Research Express and Catalysts.

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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