Narayana Santhanam
- Artificial Intelligence top 5%
- Algorithms and Data Compression 26
- Machine Learning and Algorithms 11
- Bayesian Methods and Mixture Models 10
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- Cellular Automata and Applications 13
- Computability, Logic, AI Algorithms 6
- semigroups and automata theory 3
- Statistics and Probability top 5%
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- DNA and Biological Computing 6
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- Error Correcting Code Techniques 6
- Co-authors
- Alon OrlitskyZhang Jun-anMartin J. WainwrightJ. ZhangK. ViswanathanKrishnamurthy ViswanathanA. KavcicJunan Zhang
- Journals
- IEEE Transactions on Information Theory (4 papers)IEEE Journal on Selected Areas in Communications (2 papers)Theoretical Computer Science (1 paper)
- Partner nations
- United StatesChinaGermany
In The Last Decade
Narayana Santhanam
42 papers receiving 491 citations
Peers
Comparison fields: 5 of 63
- Artificial Intelligence 391
- Computational Theory and Mathematics 166
- Statistics and Probability 80
- Signal Processing 42
- Mathematical Physics 34
Countries citing papers authored by Narayana Santhanam
This map shows the geographic impact of Narayana Santhanam'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 Narayana Santhanam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Narayana Santhanam more than expected).
Fields of papers citing papers by Narayana Santhanam
This network shows the impact of papers produced by Narayana Santhanam. 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 Narayana Santhanam. The network helps show where Narayana Santhanam may publish in the future.
Co-authorship network
The 22 scholars most cited alongside Narayana Santhanam, 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 | 2018 | 1 | |
| 2 | 2017 | 1 | |
| 3 | 2015 | 1 | |
| 4 | Proceedings of the Seventh Workshop on Information Theoretic Methods in Science and Engineering | 2014 | 2 |
| 5 | 2014 | 1 | |
| 6 | 2014 | 26 | |
| 7 | 2012 | 2 | |
| 8 | 2010 | 2 | |
| 9 | 2010 | 0 | |
| 10 | 2009 | 4 | |
| 11 | 2007 | 5 | |
| 12 | 2006 | 0 | |
| 13 | 2005 | 7 | |
| 14 | 2004 | 38 | |
| 15 | 2004 | 9 | |
| 16 | 2004 | 0 | |
| 17 | 2004 | 7 | |
| 18 | 2004 | 33 | |
| 19 | 2003 | 20 | |
| 20 | 2003 | 4 |
About Narayana Santhanam
Narayana Santhanam is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Statistics and Probability, having authored 47 papers that have together received 514 indexed citations. Recurring topics across this work include Algorithms and Data Compression (26 papers), Cellular Automata and Applications (13 papers), Machine Learning and Algorithms (11 papers), Bayesian Methods and Mixture Models (10 papers), Computability, Logic, AI Algorithms (6 papers), DNA and Biological Computing (6 papers), Error Correcting Code Techniques (6 papers) and semigroups and automata theory (3 papers). The work is most often cited by research in Artificial Intelligence (391 citations), Computational Theory and Mathematics (166 citations) and Statistics and Probability (80 citations). Narayana Santhanam has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Alon Orlitsky, Zhang Jun-an, Martin J. Wainwright, J. Zhang, K. Viswanathan, Krishnamurthy Viswanathan, A. Kavcic, Junan Zhang, Venkat Anantharam and Olgica Milenković. Their work appears in journals such as IEEE Transactions on Information Theory, IEEE Journal on Selected Areas in Communications, Theoretical Computer Science, Science and Manufacturing Engineer.
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.