A. Narayanan
- Artificial Intelligence top 5%
- Quantum Computing Algorithms and Architecture 3
- Speech and dialogue systems 1
- Neural Networks and Applications 1
- Metaheuristic Optimization Algorithms Research 1
- Bayesian Modeling and Causal Inference 1
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- Computability, Logic, AI Algorithms 2
- Control and Systems Engineering top 10%
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- Gene expression and cancer classification 3
- Gene Regulatory Network Analysis 2
- Cited by
- Artificial IntelligenceComputational Theory and MathematicsIndustrial and Manufacturing Engineering
- Journals
- Artificial Intelligence Review (2 papers)Neurocomputing (1 paper)International Joint Conference on Artificial Intelligence (1 paper)
- Partner nations
- United KingdomSweden
In The Last Decade
A. Narayanan
9 papers receiving 495 citations
Hit Papers
Peers
Comparison fields: 5 of 71
- Artificial Intelligence 353
- Computational Theory and Mathematics 63
- Industrial and Manufacturing Engineering 33
- Computer Networks and Communications 74
- Control and Systems Engineering 69
Countries citing papers authored by A. Narayanan
This map shows the geographic impact of A. Narayanan'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. Narayanan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites A. Narayanan more than expected).
Fields of papers citing papers by A. Narayanan
This network shows the impact of papers produced by A. Narayanan. 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. Narayanan. The network helps show where A. Narayanan may publish in the future.
Co-authorship network
The 6 scholars most cited alongside A. Narayanan, 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 | 2005 | 2 | |
| 2 | 2004 | 26 | |
| 3 | 2003 | 10 | |
| 4 | 2003 | 38 | |
| 5 | Quantum-inspired genetic algorithmsbreakdown → | 2002 | 440 |
| 6 | 1997 | 8 | |
| 7 | 1995 | 4 | |
| 8 | More notes on 'a clash of intuitions' | 1993 | 3 |
| 9 | 1988 | 1 | |
| 10 | An introduction to LISP | 1985 | 1 |
About A. Narayanan
A. Narayanan is a scholar working on History and Philosophy of Science, Artificial Intelligence, Computational Theory and Mathematics, Molecular Biology and Infectious Diseases, having authored 10 papers that have together received 533 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (3 papers), Gene expression and cancer classification (3 papers), Computability, Logic, AI Algorithms (2 papers), Gene Regulatory Network Analysis (2 papers), Speech and dialogue systems (1 paper), Neural Networks and Applications (1 paper), Metaheuristic Optimization Algorithms Research (1 paper) and Bayesian Modeling and Causal Inference (1 paper). The work is most often cited by research in Artificial Intelligence (353 citations), Computational Theory and Mathematics (63 citations), Industrial and Manufacturing Engineering (33 citations), Computer Networks and Communications (74 citations) and Control and Systems Engineering (69 citations). A. Narayanan has collaborated with scholars based in United Kingdom and Sweden. Frequent co-authors include Matthew Moore, Edward Keedwell, Jonas Gamalielsson, Dragan Savić, Noel Sharkey and Masoud Yazdani. Their work appears in journals such as Artificial Intelligence Review, Neurocomputing, International Joint Conference on Artificial Intelligence and Medical Entomology and Zoology.
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.