Aditya K. Prasad
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 1%
- Electrical and Electronic Engineering
- Cognitive Neuroscience top 10%
- Experimental and Cognitive Psychology top 10%
- Co-authors
- Vivek ShendeIgor L. MarkovJohn P. HayesKateri McRaeSupriya MisraJames J. GrossBenjamin Otto
- Topics
- Quantum-Dot Cellular Automata (4 papers)Quantum Computing Algorithms and Architecture (4 papers)Stress Responses and Cortisol (2 papers)
- Cited by
- Computational Theory and MathematicsArtificial IntelligenceExperimental and Cognitive Psychology
- Journals
- IEEE Transactions on Computer-Aided Design of Integrated Circuits and SystemsSocial Cognitive and Affective NeuroscienceCognitive Affective & Behavioral Neuroscience
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
Aditya K. Prasad
6 papers receiving 759 citations
Peers
Comparison fields: 5 of 65
- Artificial Intelligence 528
- Computational Theory and Mathematics 425
- Electrical and Electronic Engineering 221
- Cognitive Neuroscience 124
- Experimental and Cognitive Psychology 108
Countries citing papers authored by Aditya K. Prasad
This map shows the geographic impact of Aditya K. Prasad'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 Aditya K. Prasad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aditya K. Prasad more than expected).
Fields of papers citing papers by Aditya K. Prasad
This network shows the impact of papers produced by Aditya K. Prasad. 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 Aditya K. Prasad. The network helps show where Aditya K. Prasad may publish in the future.
Co-authorship network of co-authors of Aditya K. Prasad
This figure shows the co-authorship network connecting the top 25 collaborators of Aditya K. Prasad. A scholar is included among the top collaborators of Aditya K. Prasad 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 Aditya K. Prasad. Aditya K. Prasad is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 51 | |
| 2 | 199 | |
| 3 | 58 | |
| 4 | 356 | |
| 5 | 51 | |
| 6 | 91 |
About Aditya K. Prasad
Aditya K. Prasad is a scholar working on Behavioral Neuroscience, Computational Theory and Mathematics and Experimental and Cognitive Psychology, having authored 6 papers that have together received 806 indexed citations. Recurring topics across this work include Quantum-Dot Cellular Automata (4 papers), Quantum Computing Algorithms and Architecture (4 papers) and Stress Responses and Cortisol (2 papers). The work is most often cited by research in Computational Theory and Mathematics (425 citations), Artificial Intelligence (528 citations) and Experimental and Cognitive Psychology (108 citations). Aditya K. Prasad has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Vivek Shende, Igor L. Markov, John P. Hayes, Kateri McRae, Supriya Misra, James J. Gross and Benjamin Otto. Their work appears in journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Social Cognitive and Affective Neuroscience and Cognitive Affective & Behavioral Neuroscience.
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.