Aditya Shukla
- Electrical and Electronic Engineering
- Artificial Intelligence top 10%
- Cellular and Molecular Neuroscience
- Cognitive Neuroscience
- Computer Vision and Pattern Recognition
- Co-authors
- Udayan GangulyNihar R. MohapatraVinay KumarShirish ShevadeVinod GanapathyAditya KanadeVimal KumarMikhail Erementchouk
- Topics
- Advanced Memory and Neural Computing (6 papers)Neural dynamics and brain function (3 papers)Quantum Computing Algorithms and Architecture (3 papers)
- Partner nations
- IndiaUnited States
In The Last Decade
Aditya Shukla
14 papers receiving 269 citations
Peers
Comparison fields: 5 of 41
- Electrical and Electronic Engineering 183
- Artificial Intelligence 130
- Cellular and Molecular Neuroscience 73
- Cognitive Neuroscience 62
- Computer Vision and Pattern Recognition 18
Countries citing papers authored by Aditya Shukla
This map shows the geographic impact of Aditya Shukla'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 Shukla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Aditya Shukla more than expected).
Fields of papers citing papers by Aditya Shukla
This network shows the impact of papers produced by Aditya Shukla. 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 Shukla. The network helps show where Aditya Shukla may publish in the future.
Co-authorship network of co-authors of Aditya Shukla
This figure shows the co-authorship network connecting the top 25 collaborators of Aditya Shukla. A scholar is included among the top collaborators of Aditya Shukla 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 Shukla. Aditya Shukla 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 | 0 | |
| 6 | 10 | |
| 7 | 0 | |
| 8 | 2 | |
| 9 | 1 | |
| 10 | 60 | |
| 11 | Control and Implementation of Bi-Directional Converter for Power Management of Unbalanced DC Microgrid | 2 |
| 12 | 1 | |
| 13 | 15 | |
| 14 | A Real-time Trainable and Clock-less Spiking Neural Network with 1R Memristive Synapses. | 1 |
| 15 | 154 | |
| 16 | 17 | |
| 17 | 6 | |
| 18 | 1 |
About Aditya Shukla
Aditya Shukla is a scholar working on Energy Engineering and Power Technology, Software and Electrical and Electronic Engineering, having authored 18 papers that have together received 273 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (6 papers), Neural dynamics and brain function (3 papers) and Quantum Computing Algorithms and Architecture (3 papers). The work is most often cited by research in Artificial Intelligence (130 citations), Cellular and Molecular Neuroscience (73 citations) and Cognitive Neuroscience (62 citations). Aditya Shukla has collaborated with scholars based in India and United States. Frequent co-authors include Udayan Ganguly, Nihar R. Mohapatra, Vinay Kumar, Shirish Shevade, Vinod Ganapathy, Aditya Kanade, Vimal Kumar, Mikhail Erementchouk, Pinaki Mazumder and Navdeep Singh. Their work appears in journals such as Scientific Reports, IEEE Transactions on Computers and Physica D Nonlinear Phenomena.
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.