A. Chandrasekar
- Computer Networks and Communications top 1%
- Statistical and Nonlinear Physics top 1%
- Electrical and Electronic Engineering top 10%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 5%
- Co-authors
- R. RakkiyappanJinde CaoQuanxin ZhuT. RadhikaS. LakshmananJu H. ParkV. VijayakumarYang Cao
- Topics
- Neural Networks Stability and Synchronization (30 papers)stochastic dynamics and bifurcation (13 papers)Advanced Memory and Neural Computing (9 papers)
- Cited by
- Computer Networks and CommunicationsStatistical and Nonlinear PhysicsControl and Systems Engineering
- Journals
- IEEE Transactions on Neural Networks and Learning SystemsNeurocomputingJournal of the Franklin Institute
- Partner nations
- IndiaChinaUnited Arab Emirates
In The Last Decade
A. Chandrasekar
33 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 86
- Computer Networks and Communications 1.2k
- Statistical and Nonlinear Physics 569
- Electrical and Electronic Engineering 486
- Artificial Intelligence 457
- Control and Systems Engineering 379
Countries citing papers authored by A. Chandrasekar
This map shows the geographic impact of A. Chandrasekar'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 A. Chandrasekar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Chandrasekar more than expected).
Fields of papers citing papers by A. Chandrasekar
This network shows the impact of papers produced by A. Chandrasekar. 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 A. Chandrasekar. The network helps show where A. Chandrasekar may publish in the future.
Co-authorship network of co-authors of A. Chandrasekar
This figure shows the co-authorship network connecting the top 25 collaborators of A. Chandrasekar. A scholar is included among the top collaborators of A. Chandrasekar 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 A. Chandrasekar. A. Chandrasekar 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 11 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 40 | |
| 10 | 36 | |
| 11 | 56 | |
| 12 | 105 | |
| 13 | 14 | |
| 14 | 144 | |
| 15 | 50 | |
| 16 | 23 | |
| 17 | 22 | |
| 18 | 104 | |
| 19 | 122 | |
| 20 | 44 |
About A. Chandrasekar
A. Chandrasekar is a scholar working on Computer Networks and Communications, Statistical and Nonlinear Physics and Control and Systems Engineering, having authored 38 papers that have together received 1.7k indexed citations. Recurring topics across this work include Neural Networks Stability and Synchronization (30 papers), stochastic dynamics and bifurcation (13 papers) and Advanced Memory and Neural Computing (9 papers). The work is most often cited by research in Computer Networks and Communications (1.2k citations), Statistical and Nonlinear Physics (569 citations) and Control and Systems Engineering (379 citations). A. Chandrasekar has collaborated with scholars based in India, China and United Arab Emirates. Frequent co-authors include R. Rakkiyappan, Jinde Cao, Quanxin Zhu, T. Radhika, S. Lakshmanan, Ju H. Park, V. Vijayakumar, Yang Cao, Fathalla A. Rihan and R. Krishnasamy. Their work appears in journals such as IEEE Transactions on Neural Networks and Learning Systems, Neurocomputing and Journal of the Franklin Institute.
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.