S. Chandrasekaran
- Computer Vision and Pattern Recognition top 2%
- Computational Theory and Mathematics top 5%
- Artificial Intelligence top 10%
- Signal Processing top 5%
- Control and Systems Engineering top 10%
- Co-authors
- B.S. ManjunathAli H. SayedUpamanyu MadhowMing GuKaushal SolankiKyle T. SullivanGene H. GolubS. Venkatesan
- Topics
- Advanced Steganography and Watermarking Techniques (12 papers)Chaos-based Image/Signal Encryption (11 papers)Digital Media Forensic Detection (9 papers)
- Journals
- Journal of Computational PhysicsIEEE Transactions on Image ProcessingIEEE Transactions on Signal Processing
- Partner nations
- United StatesIndiaSwitzerland
In The Last Decade
S. Chandrasekaran
41 papers receiving 909 citations
Peers
Comparison fields: 5 of 83
- Computer Vision and Pattern Recognition 554
- Computational Theory and Mathematics 160
- Artificial Intelligence 140
- Signal Processing 117
- Control and Systems Engineering 116
Countries citing papers authored by S. Chandrasekaran
This map shows the geographic impact of S. Chandrasekaran'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 S. Chandrasekaran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. Chandrasekaran more than expected).
Fields of papers citing papers by S. Chandrasekaran
This network shows the impact of papers produced by S. Chandrasekaran. 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 S. Chandrasekaran. The network helps show where S. Chandrasekaran may publish in the future.
Co-authorship network of co-authors of S. Chandrasekaran
This figure shows the co-authorship network connecting the top 25 collaborators of S. Chandrasekaran. A scholar is included among the top collaborators of S. Chandrasekaran 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 S. Chandrasekaran. S. Chandrasekaran is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 18 | |
| 2 | 1 | |
| 3 | CAR based safety model in automotive software engineering | 2 |
| 4 | An adaptive trust model for software services in hybrid cloud environment | 4 |
| 5 | 7 | |
| 6 | 3 | |
| 7 | An Artificial Immune Networking Using Intelligent Agents | 1 |
| 8 | 9 | |
| 9 | 10 | |
| 10 | 97 | |
| 11 | 51 | |
| 12 | 23 | |
| 13 | 8 | |
| 14 | 17 | |
| 15 | 35 | |
| 16 | 97 | |
| 17 | 36 | |
| 18 | 3 | |
| 19 | 163 | |
| 20 | 40 |
About S. Chandrasekaran
S. Chandrasekaran is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Applied Mathematics, having authored 43 papers that have together received 1.1k indexed citations. Recurring topics across this work include Advanced Steganography and Watermarking Techniques (12 papers), Chaos-based Image/Signal Encryption (11 papers) and Digital Media Forensic Detection (9 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (554 citations), Computational Mathematics (11 citations) and Numerical Analysis (76 citations). S. Chandrasekaran has collaborated with scholars based in United States, India and Switzerland. Frequent co-authors include B.S. Manjunath, Ali H. Sayed, Upamanyu Madhow, Ming Gu, Kaushal Solanki, Kyle T. Sullivan, Gene H. Golub, S. Venkatesan, B. S. Manjunath and Onkar Dabeer. Their work appears in journals such as Journal of Computational Physics, IEEE Transactions on Image Processing and IEEE Transactions on Signal Processing.
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.