Jainendra Shukla
- Cognitive Neuroscience top 10%
- Experimental and Cognitive Psychology top 10%
- Social Psychology
- Artificial Intelligence
- Cardiology and Cardiovascular Medicine
- Co-authors
- Joan Guix OliverDomènec PuigMiguel Barreda-ÁngelesG. C. NandiAman ParnamiSumita SharmaGrace EdenDeepa Singh
- Topics
- Emotion and Mood Recognition (10 papers)EEG and Brain-Computer Interfaces (9 papers)Autism Spectrum Disorder Research (7 papers)
- Journals
- Scientific ReportsIEEE Transactions on Instrumentation and MeasurementComputers in Biology and Medicine
- Partner nations
- IndiaSpainNetherlands
In The Last Decade
Jainendra Shukla
26 papers receiving 345 citations
Peers
Comparison fields: 5 of 75
- Cognitive Neuroscience 175
- Experimental and Cognitive Psychology 153
- Social Psychology 76
- Artificial Intelligence 59
- Cardiology and Cardiovascular Medicine 54
Countries citing papers authored by Jainendra Shukla
This map shows the geographic impact of Jainendra 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 Jainendra Shukla with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jainendra Shukla more than expected).
Fields of papers citing papers by Jainendra Shukla
This network shows the impact of papers produced by Jainendra 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 Jainendra Shukla. The network helps show where Jainendra Shukla may publish in the future.
Co-authorship network of co-authors of Jainendra Shukla
This figure shows the co-authorship network connecting the top 25 collaborators of Jainendra Shukla. A scholar is included among the top collaborators of Jainendra 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 Jainendra Shukla. Jainendra 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 | 0 | |
| 2 | 0 | |
| 3 | 2 | |
| 4 | 6 | |
| 5 | 0 | |
| 6 | 1 | |
| 7 | 2 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 0 | |
| 11 | 3 | |
| 12 | 1 | |
| 13 | 13 | |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 4 | |
| 17 | 1 | |
| 18 | 18 | |
| 19 | 164 | |
| 20 | 31 |
About Jainendra Shukla
Jainendra Shukla is a scholar working on Cognitive Neuroscience, Experimental and Cognitive Psychology and Human-Computer Interaction, having authored 32 papers that have together received 353 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (10 papers), EEG and Brain-Computer Interfaces (9 papers) and Autism Spectrum Disorder Research (7 papers). The work is most often cited by research in Experimental and Cognitive Psychology (153 citations), Cognitive Neuroscience (175 citations) and Human-Computer Interaction (49 citations). Jainendra Shukla has collaborated with scholars based in India, Spain and Netherlands. Frequent co-authors include Joan Guix Oliver, Domènec Puig, Miguel Barreda-Ángeles, G. C. Nandi, Aman Parnami, Sumita Sharma, Grace Eden, Deepa Singh, Eduard Fosch‐Villaronga and N. Ramasubramanian. Their work appears in journals such as Scientific Reports, IEEE Transactions on Instrumentation and Measurement and Computers in Biology and Medicine.
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.