Paliath Narendran
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 1%
- Molecular Biology
- Geometry and Topology top 5%
- Computer Networks and Communications top 10%
- Co-authors
- Deepak KapurFriedrich OttoRobert McNaughtonHantao ZhangWayne SnyderJean GallierMichaël RusinowitchDavid A. Plaisted
- Topics
- Logic, programming, and type systems (39 papers)semigroups and automata theory (37 papers)Formal Methods in Verification (16 papers)
- Partner nations
- United StatesGermanyFrance
In The Last Decade
Paliath Narendran
64 papers receiving 665 citations
Peers
Comparison fields: 5 of 32
- Artificial Intelligence 612
- Computational Theory and Mathematics 577
- Molecular Biology 91
- Geometry and Topology 88
- Computer Networks and Communications 76
Countries citing papers authored by Paliath Narendran
This map shows the geographic impact of Paliath Narendran'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 Paliath Narendran with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paliath Narendran more than expected).
Fields of papers citing papers by Paliath Narendran
This network shows the impact of papers produced by Paliath Narendran. 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 Paliath Narendran. The network helps show where Paliath Narendran may publish in the future.
Co-authorship network of co-authors of Paliath Narendran
This figure shows the co-authorship network connecting the top 25 collaborators of Paliath Narendran. A scholar is included among the top collaborators of Paliath Narendran 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 Paliath Narendran. Paliath Narendran 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 | 1 | |
| 3 | 0 | |
| 4 | Texture analysis on low resolution images using unsupervised segmentation algorithm with multichannel Local Frequency analysis | 1 |
| 5 | An E-unification algorithm for analyzing protocols that use modular exponentiation | 0 |
| 6 | 6 | |
| 7 | Rewriting Techniques & Applications | 1 |
| 8 | 19 | |
| 9 | 6 | |
| 10 | 25 | |
| 11 | 2 | |
| 12 | 4 | |
| 13 | 5 | |
| 14 | 9 | |
| 15 | An equational approach to theorem proving in first-order predicate calculus | 37 |
| 16 | 12 | |
| 17 | 37 | |
| 18 | 15 | |
| 19 | 9 | |
| 20 | 6 |
About Paliath Narendran
Paliath Narendran is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Geometry and Topology, having authored 72 papers that have together received 743 indexed citations. Recurring topics across this work include Logic, programming, and type systems (39 papers), semigroups and automata theory (37 papers) and Formal Methods in Verification (16 papers). The work is most often cited by research in Computational Theory and Mathematics (577 citations), Artificial Intelligence (612 citations) and Software (41 citations). Paliath Narendran has collaborated with scholars based in United States, Germany and France. Frequent co-authors include Deepak Kapur, Friedrich Otto, Robert McNaughton, Hantao Zhang, Wayne Snyder, Jean Gallier, Michaël Rusinowitch, David A. Plaisted, Mukkai S. Krishnamoorthy and Colm Ó'Dúnlaing. Their work appears in journals such as Journal of the ACM, SIAM Journal on Computing and Theoretical Computer Science.
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.