Suresh Sundaram
- Artificial Intelligence top 0.2%
- Neural Networks and Applications 68
- Machine Learning and ELM 36
- Fuzzy Logic and Control Systems 32
- Metaheuristic Optimization Algorithms Research 23
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- Robotic Path Planning Algorithms 23
- Cognitive Neuroscience top 2%
- EEG and Brain-Computer Interfaces 21
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- Adaptive Control of Nonlinear Systems 23
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- Advanced Multi-Objective Optimization Algorithms 19
Suresh Sundaram
283 papers receiving 6.1k citations
Hit Papers
Peers
Comparison fields: 5 of 162
- Artificial Intelligence 2.9k
- Computer Vision and Pattern Recognition 1.8k
- Cognitive Neuroscience 739
- Control and Systems Engineering 828
- Computational Theory and Mathematics 488
Countries citing papers authored by Suresh Sundaram
This map shows the geographic impact of Suresh Sundaram'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 Suresh Sundaram with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suresh Sundaram more than expected).
Fields of papers citing papers by Suresh Sundaram
This network shows the impact of papers produced by Suresh Sundaram. 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 Suresh Sundaram. The network helps show where Suresh Sundaram may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Suresh Sundaram, 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 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2025 | 2 | |
| 4 | 2025 | 1 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 4 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 0 | |
| 9 | 2024 | 0 | |
| 10 | 2024 | 1 | |
| 11 | 2024 | 0 | |
| 12 | 2024 | 1 | |
| 13 | 2024 | 2 | |
| 14 | 2022 | 15 | |
| 15 | 2022 | 28 | |
| 16 | 2018 | 24 | |
| 17 | 2017 | 18 | |
| 18 | 2016 | 1 | |
| 19 | Mathematical model and rule extraction for tool wear monitoring problem using nature inspired techniques | 2009 | 2 |
| 20 | 2003 | 18 |
About Suresh Sundaram
Suresh Sundaram is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Aerospace Engineering, Control and Systems Engineering and Computational Theory and Mathematics, having authored 307 papers that have together received 6.4k indexed citations. Recurring topics across this work include Neural Networks and Applications (68 papers), Machine Learning and ELM (36 papers), Fuzzy Logic and Control Systems (32 papers), Adaptive Control of Nonlinear Systems (23 papers), Robotic Path Planning Algorithms (23 papers), Metaheuristic Optimization Algorithms Research (23 papers), EEG and Brain-Computer Interfaces (21 papers) and Advanced Multi-Objective Optimization Algorithms (19 papers). The work is most often cited by research in Artificial Intelligence (2.9k citations), Computer Vision and Pattern Recognition (1.8k citations), Cognitive Neuroscience (739 citations), Control and Systems Engineering (828 citations) and Computational Theory and Mathematics (488 citations). Suresh Sundaram has collaborated with scholars based in Singapore, India and United States. Frequent co-authors include N. Sundararajan, Savitha Ramasamy, K. R. Subramanian, G. S. D. Babu, Muhammad Rizwan Tanweer, N. Sundararajan, Vasily Sachnev, Yun Q. Shi, Jeho Nam and R. Venkatesh Babu. Their work appears in journals such as Neurocomputing, Applied Soft Computing, Information Sciences, Expert Systems with Applications and Cognitive Computation.
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.