Rupesh K. Srivastava
- Artificial Intelligence top 0.5%
- Computer Vision and Pattern Recognition top 0.5%
- Molecular Biology top 5%
- Electrical and Electronic Engineering top 5%
- Signal Processing top 1%
- Co-authors
- Jürgen SchmidhuberBas R. SteunebrinkKlaus GreffJan KoutníkPradyumna Kumar MishraHamid Y. DarLeena SapraGeetanjali B. Tomar
- Topics
- Bone Metabolism and Diseases (20 papers)Biomarkers in Disease Mechanisms (7 papers)Psoriasis: Treatment and Pathogenesis (6 papers)
- Journals
- Nature CommunicationsSHILAP Revista de lepidopterologíaThe Journal of Immunology
- Partner nations
- IndiaUnited StatesSwitzerland
In The Last Decade
Rupesh K. Srivastava
103 papers receiving 7.8k citations
Hit Papers
Peers
Comparison fields: 5 of 219
- Artificial Intelligence 2.1k
- Computer Vision and Pattern Recognition 1.5k
- Molecular Biology 1.4k
- Electrical and Electronic Engineering 872
- Signal Processing 543
Countries citing papers authored by Rupesh K. Srivastava
This map shows the geographic impact of Rupesh K. Srivastava'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 Rupesh K. Srivastava with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rupesh K. Srivastava more than expected).
Fields of papers citing papers by Rupesh K. Srivastava
This network shows the impact of papers produced by Rupesh K. Srivastava. 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 Rupesh K. Srivastava. The network helps show where Rupesh K. Srivastava may publish in the future.
Co-authorship network of co-authors of Rupesh K. Srivastava
This figure shows the co-authorship network connecting the top 25 collaborators of Rupesh K. Srivastava. A scholar is included among the top collaborators of Rupesh K. Srivastava 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 Rupesh K. Srivastava. Rupesh K. Srivastava is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 7 | |
| 2 | 3 | |
| 3 | 15 | |
| 4 | 14 | |
| 5 | 9 | |
| 6 | 28 | |
| 7 | 4 | |
| 8 | 9 | |
| 9 | 27 | |
| 10 | 26 | |
| 11 | 17 | |
| 12 | 2 | |
| 13 | 2 | |
| 14 | 64 | |
| 15 | 247 | |
| 16 | LSTM: A Search Space Odysseybreakdown → | 4435 |
| 17 | Compete to Compute | 51 |
| 18 | 10 | |
| 19 | 6 | |
| 20 | Effect of spray cooling and wallowing on blood composition in buffaloes during summer. | 2 |
About Rupesh K. Srivastava
Rupesh K. Srivastava is a scholar working on Immunology, Pharmacology and Molecular Biology, having authored 109 papers that have together received 8.0k indexed citations. Recurring topics across this work include Bone Metabolism and Diseases (20 papers), Biomarkers in Disease Mechanisms (7 papers) and Psoriasis: Treatment and Pathogenesis (6 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.5k citations), Artificial Intelligence (2.1k citations) and Signal Processing (543 citations). Rupesh K. Srivastava has collaborated with scholars based in India, United States and Switzerland. Frequent co-authors include Jürgen Schmidhuber, Bas R. Steunebrink, Klaus Greff, Jan Koutník, Pradyumna Kumar Mishra, Hamid Y. Dar, Leena Sapra, Geetanjali B. Tomar, Gyan C. Mishra and Saurabh Gupta. Their work appears in journals such as Nature Communications, SHILAP Revista de lepidopterología and The Journal of Immunology.
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.