K. G. Subramanian
- Mechanical Engineering top 5%
- Materials Chemistry top 10%
- Molecular Biology
- Mechanics of Materials top 5%
- Electrical and Electronic Engineering
- Co-authors
- Ashish Kumar NathRani SiromoneyE. SchulzT. RamanathanAlexander BismarckIbrahim VenkatA.V.R. ReddyK. S. Sastri
- Topics
- DNA and Biological Computing (73 papers)Modular Robots and Swarm Intelligence (42 papers)Algorithms and Data Compression (27 papers)
- Journals
- Materials Science and Engineering AJournal of Materials ScienceIndustrial & Engineering Chemistry Research
- Partner nations
- IndiaUnited KingdomMalaysia
In The Last Decade
K. G. Subramanian
145 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 116
- Mechanical Engineering 608
- Materials Chemistry 449
- Molecular Biology 417
- Mechanics of Materials 343
- Electrical and Electronic Engineering 274
Countries citing papers authored by K. G. Subramanian
This map shows the geographic impact of K. G. Subramanian'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 K. G. Subramanian with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites K. G. Subramanian more than expected).
Fields of papers citing papers by K. G. Subramanian
This network shows the impact of papers produced by K. G. Subramanian. 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 K. G. Subramanian. The network helps show where K. G. Subramanian may publish in the future.
Co-authorship network of co-authors of K. G. Subramanian
This figure shows the co-authorship network connecting the top 25 collaborators of K. G. Subramanian. A scholar is included among the top collaborators of K. G. Subramanian based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with K. G. Subramanian. K. G. Subramanian is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 12 | |
| 3 | 1 | |
| 4 | 3 | |
| 5 | 3 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 5 | |
| 11 | Two-dimensional pattern languages. | 0 |
| 12 | 31 | |
| 13 | 3 | |
| 14 | 6 | |
| 15 | 14 | |
| 16 | On the Inference of Linear Single Tree Grammars from Positive Structural Information. | 0 |
| 17 | P SYSTEMS FOR ARRAY GENERATION AND APPLICATION TO KOLAM PATTERNS | 13 |
| 18 | Learning of Regular Bi-omega Languages | 1 |
| 19 | Regular control on NLC grammars. | 1 |
| 20 | 4 |
About K. G. Subramanian
K. G. Subramanian is a scholar working on Computational Theory and Mathematics, Mechanical Engineering and Discrete Mathematics and Combinatorics, having authored 159 papers that have together received 1.7k indexed citations. Recurring topics across this work include DNA and Biological Computing (73 papers), Modular Robots and Swarm Intelligence (42 papers) and Algorithms and Data Compression (27 papers). The work is most often cited by research in Metals and Alloys (51 citations), Computational Theory and Mathematics (268 citations) and Polymers and Plastics (235 citations). K. G. Subramanian has collaborated with scholars based in India, United Kingdom and Malaysia. Frequent co-authors include Ashish Kumar Nath, Rani Siromoney, E. Schulz, T. Ramanathan, Alexander Bismarck, Ibrahim Venkat, A.V.R. Reddy, K. S. Sastri, Malathy Pushpavanam and V. Krishnasamy. Their work appears in journals such as Materials Science and Engineering A, Journal of Materials Science and Industrial & Engineering Chemistry Research.
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.