Subramaniam Ganesan
- Computer Networks and Communications top 5%
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 5%
- Co-authors
- Vishnu KamatMajed AborokbahSaad AlmutairiS. ManimuruganNaveen ChilamkurtiRizwan PatanMichael PechtMichael Osterman
- Topics
- Electronic Packaging and Soldering Technologies (9 papers)Embedded Systems Design Techniques (8 papers)Autonomous Vehicle Technology and Safety (6 papers)
- Partner nations
- United StatesIndiaSaudi Arabia
In The Last Decade
Subramaniam Ganesan
89 papers receiving 1.0k citations
Peers
Comparison fields: 5 of 111
- Computer Networks and Communications 262
- Electrical and Electronic Engineering 246
- Computer Vision and Pattern Recognition 234
- Artificial Intelligence 209
- Control and Systems Engineering 159
Countries citing papers authored by Subramaniam Ganesan
This map shows the geographic impact of Subramaniam Ganesan'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 Subramaniam Ganesan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Subramaniam Ganesan more than expected).
Fields of papers citing papers by Subramaniam Ganesan
This network shows the impact of papers produced by Subramaniam Ganesan. 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 Subramaniam Ganesan. The network helps show where Subramaniam Ganesan may publish in the future.
Co-authorship network of co-authors of Subramaniam Ganesan
This figure shows the co-authorship network connecting the top 25 collaborators of Subramaniam Ganesan. A scholar is included among the top collaborators of Subramaniam Ganesan 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 Subramaniam Ganesan. Subramaniam Ganesan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 9 | |
| 6 | 3 | |
| 7 | 55 | |
| 8 | 4 | |
| 9 | 2 | |
| 10 | 10 | |
| 11 | 19 | |
| 12 | 2 | |
| 13 | 159 | |
| 14 | 5 | |
| 15 | 13 | |
| 16 | 26 | |
| 17 | 27 | |
| 18 | 7 | |
| 19 | 1 | |
| 20 | 1 |
About Subramaniam Ganesan
Subramaniam Ganesan is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computer Vision and Pattern Recognition, having authored 108 papers that have together received 1.1k indexed citations. Recurring topics across this work include Electronic Packaging and Soldering Technologies (9 papers), Embedded Systems Design Techniques (8 papers) and Autonomous Vehicle Technology and Safety (6 papers). The work is most often cited by research in Medical Laboratory Technology (36 citations), Media Technology (139 citations) and Signal Processing (140 citations). Subramaniam Ganesan has collaborated with scholars based in United States, India and Saudi Arabia. Frequent co-authors include Vishnu Kamat, Majed Aborokbah, Saad Almutairi, S. Manimurugan, Naveen Chilamkurti, Rizwan Patan, Michael Pecht, Michael Osterman, Fayadh Alenezi and C. Narmatha. Their work appears in journals such as Nature, PLoS ONE and Expert Systems with Applications.
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.