N. Sundararajan
- Artificial Intelligence top 0.2%
- Control and Systems Engineering top 0.5%
- Electrical and Electronic Engineering top 5%
- Computer Vision and Pattern Recognition top 1%
- Cognitive Neuroscience top 5%
- Co-authors
- P. SaratchandranSuresh SundaramGuang-Bin HuangHai-Jun RongSavitha RamasamyMuhammad Rizwan TanweerNanying LiangRunxuan Zhang
- Topics
- Neural Networks and Applications (67 papers)Machine Learning and ELM (30 papers)Adaptive Control of Nonlinear Systems (25 papers)
- Partner nations
- SingaporeIndiaUnited States
In The Last Decade
N. Sundararajan
173 papers receiving 5.3k citations
Peers
Comparison fields: 5 of 161
- Artificial Intelligence 3.5k
- Control and Systems Engineering 1.5k
- Electrical and Electronic Engineering 995
- Computer Vision and Pattern Recognition 793
- Cognitive Neuroscience 587
Countries citing papers authored by N. Sundararajan
This map shows the geographic impact of N. Sundararajan'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 N. Sundararajan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites N. Sundararajan more than expected).
Fields of papers citing papers by N. Sundararajan
This network shows the impact of papers produced by N. Sundararajan. 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 N. Sundararajan. The network helps show where N. Sundararajan may publish in the future.
Co-authorship network of co-authors of N. Sundararajan
This figure shows the co-authorship network connecting the top 25 collaborators of N. Sundararajan. A scholar is included among the top collaborators of N. Sundararajan 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 N. Sundararajan. N. Sundararajan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 4 | |
| 4 | 1 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 15 | |
| 9 | 0 | |
| 10 | 28 | |
| 11 | 61 | |
| 12 | 7 | |
| 13 | 48 | |
| 14 | 44 | |
| 15 | 277 | |
| 16 | 147 | |
| 17 | 88 | |
| 18 | 17 | |
| 19 | 8 | |
| 20 | 9 |
About N. Sundararajan
N. Sundararajan is a scholar working on Artificial Intelligence, Control and Systems Engineering and Signal Processing, having authored 181 papers that have together received 5.5k indexed citations. Recurring topics across this work include Neural Networks and Applications (67 papers), Machine Learning and ELM (30 papers) and Adaptive Control of Nonlinear Systems (25 papers). The work is most often cited by research in Artificial Intelligence (3.5k citations), Control and Systems Engineering (1.5k citations) and Signal Processing (452 citations). N. Sundararajan has collaborated with scholars based in Singapore, India and United States. Frequent co-authors include P. Saratchandran, Suresh Sundaram, Guang-Bin Huang, Hai-Jun Rong, Savitha Ramasamy, Muhammad Rizwan Tanweer, Nanying Liang, Runxuan Zhang, K. R. Subramanian and Abhay A. Pashilkar. Their work appears in journals such as IEEE Transactions on Automatic Control, Automatica 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.