Kanishka Tyagi
- Electrical and Electronic Engineering
- Renewable Energy, Sustainability and the Environment top 10%
- Pollution top 10%
- Control and Systems Engineering top 10%
- Mechanical Engineering
- Co-authors
- M.T. ManryXun CaiPrem KalraSandeep YadavNojun KwakZhi ChenDeepak MishraShan Zhang
- Topics
- Neural Networks and Applications (17 papers)Blind Source Separation Techniques (6 papers)Machine Learning and ELM (4 papers)
- Cited by
- Energy Engineering and Power TechnologyGeneral EnergyRenewable Energy, Sustainability and the Environment
- Journals
- IEEE Transactions on Instrumentation and MeasurementNeural Processing LettersEvolutionary Intelligence
- Partner nations
- United StatesIndiaChina
In The Last Decade
Kanishka Tyagi
27 papers receiving 365 citations
Peers
Comparison fields: 5 of 57
- Electrical and Electronic Engineering 150
- Renewable Energy, Sustainability and the Environment 146
- Pollution 103
- Control and Systems Engineering 77
- Mechanical Engineering 72
Countries citing papers authored by Kanishka Tyagi
This map shows the geographic impact of Kanishka Tyagi'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 Kanishka Tyagi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kanishka Tyagi more than expected).
Fields of papers citing papers by Kanishka Tyagi
This network shows the impact of papers produced by Kanishka Tyagi. 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 Kanishka Tyagi. The network helps show where Kanishka Tyagi may publish in the future.
Co-authorship network of co-authors of Kanishka Tyagi
This figure shows the co-authorship network connecting the top 25 collaborators of Kanishka Tyagi. A scholar is included among the top collaborators of Kanishka Tyagi 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 Kanishka Tyagi. Kanishka Tyagi 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 | 8 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 12 | |
| 7 | 11 | |
| 8 | 9 | |
| 9 | 4 | |
| 10 | 33 | |
| 11 | 24 | |
| 12 | 24 | |
| 13 | 28 | |
| 14 | 23 | |
| 15 | 30 | |
| 16 | 30 | |
| 17 | Second Order Training Algorithms For Radial Basis Function Neural Networks | 33 |
| 18 | 31 | |
| 19 | 33 | |
| 20 | 22 |
About Kanishka Tyagi
Kanishka Tyagi is a scholar working on Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 28 papers that have together received 554 indexed citations. Recurring topics across this work include Neural Networks and Applications (17 papers), Blind Source Separation Techniques (6 papers) and Machine Learning and ELM (4 papers). The work is most often cited by research in Energy Engineering and Power Technology (67 citations), General Energy (10 citations) and Renewable Energy, Sustainability and the Environment (146 citations). Kanishka Tyagi has collaborated with scholars based in United States, India and China. Frequent co-authors include M.T. Manry, Xun Cai, Prem Kalra, Sandeep Yadav, Nojun Kwak, Zhi Chen, Deepak Mishra, Shan Zhang, Yilong Hao and Ziqiang Li. Their work appears in journals such as IEEE Transactions on Instrumentation and Measurement, Neural Processing Letters and Evolutionary Intelligence.
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.