Akhilesh Jaiswal
- Electrical and Electronic Engineering top 2%
- Artificial Intelligence top 2%
- Cognitive Neuroscience top 5%
- Cellular and Molecular Neuroscience top 5%
- Atomic and Molecular Physics, and Optics top 10%
- Co-authors
- Kaushik RoyPriyadarshini PandaAmogh AgrawalChankyu LeeMustafa AliIndranil ChakrabortyAtanu SahaSumeet K. Gupta
- Topics
- Advanced Memory and Neural Computing (44 papers)Ferroelectric and Negative Capacitance Devices (28 papers)CCD and CMOS Imaging Sensors (11 papers)
- Cited by
- Electrical and Electronic EngineeringCognitive NeuroscienceCellular and Molecular Neuroscience
- Partner nations
- United StatesSouth KoreaUnited Kingdom
In The Last Decade
Akhilesh Jaiswal
52 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 81
- Electrical and Electronic Engineering 2.1k
- Artificial Intelligence 660
- Cognitive Neuroscience 503
- Cellular and Molecular Neuroscience 422
- Atomic and Molecular Physics, and Optics 187
Countries citing papers authored by Akhilesh Jaiswal
This map shows the geographic impact of Akhilesh Jaiswal'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 Akhilesh Jaiswal with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akhilesh Jaiswal more than expected).
Fields of papers citing papers by Akhilesh Jaiswal
This network shows the impact of papers produced by Akhilesh Jaiswal. 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 Akhilesh Jaiswal. The network helps show where Akhilesh Jaiswal may publish in the future.
Co-authorship network of co-authors of Akhilesh Jaiswal
This figure shows the co-authorship network connecting the top 25 collaborators of Akhilesh Jaiswal. A scholar is included among the top collaborators of Akhilesh Jaiswal 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 Akhilesh Jaiswal. Akhilesh Jaiswal is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 8 | |
| 6 | 0 | |
| 7 | 3 | |
| 8 | 6 | |
| 9 | 12 | |
| 10 | 3 | |
| 11 | 21 | |
| 12 | 32 | |
| 13 | Towards spike-based machine intelligence with neuromorphic computingbreakdown → | 1321 |
| 14 | 9 | |
| 15 | 16 | |
| 16 | 9 | |
| 17 | 15 | |
| 18 | 2 | |
| 19 | 39 | |
| 20 | 21 |
About Akhilesh Jaiswal
Akhilesh Jaiswal is a scholar working on Computational Mathematics, Electrical and Electronic Engineering and Atomic and Molecular Physics, and Optics, having authored 60 papers that have together received 2.4k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (44 papers), Ferroelectric and Negative Capacitance Devices (28 papers) and CCD and CMOS Imaging Sensors (11 papers). The work is most often cited by research in Electrical and Electronic Engineering (2.1k citations), Cognitive Neuroscience (503 citations) and Cellular and Molecular Neuroscience (422 citations). Akhilesh Jaiswal has collaborated with scholars based in United States, South Korea and United Kingdom. Frequent co-authors include Kaushik Roy, Priyadarshini Panda, Amogh Agrawal, Chankyu Lee, Mustafa Ali, Indranil Chakraborty, Atanu Saha, Sumeet K. Gupta, Abhronil Sengupta and Yong Shim. Their work appears in journals such as Nature, Applied Physics Letters and Journal of Applied Physics.
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.