Subodh Srivastava
- Computer Vision and Pattern Recognition top 5%
- Health, Toxicology and Mutagenesis top 5%
- Artificial Intelligence top 5%
- Biomedical Engineering
- Materials Chemistry
- Co-authors
- Rajeev SrivastavaRajesh Kumar DhanarajV. K. DuaNiraj PantD. K. SaxenaNachiappan ChockalingamN. MathurY. K. Vijay
- Topics
- Analytical Chemistry and Chromatography (28 papers)Image and Signal Denoising Methods (25 papers)AI in cancer detection (18 papers)
- Cited by
- Health, Toxicology and MutagenesisComputer Vision and Pattern RecognitionAnalytical Chemistry
- Journals
- Journal of Biological ChemistrySHILAP Revista de lepidopterologíaThe Science of The Total Environment
- Partner nations
- IndiaUnited KingdomUnited States
In The Last Decade
Subodh Srivastava
159 papers receiving 1.6k citations
Peers
Comparison fields: 5 of 158
- Computer Vision and Pattern Recognition 318
- Health, Toxicology and Mutagenesis 285
- Artificial Intelligence 265
- Biomedical Engineering 216
- Materials Chemistry 184
Countries citing papers authored by Subodh Srivastava
This map shows the geographic impact of Subodh 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 Subodh Srivastava with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Subodh Srivastava more than expected).
Fields of papers citing papers by Subodh Srivastava
This network shows the impact of papers produced by Subodh 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 Subodh Srivastava. The network helps show where Subodh Srivastava may publish in the future.
Co-authorship network of co-authors of Subodh Srivastava
This figure shows the co-authorship network connecting the top 25 collaborators of Subodh Srivastava. A scholar is included among the top collaborators of Subodh 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 Subodh Srivastava. Subodh 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 | 4 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 3 | |
| 5 | 0 | |
| 6 | 6 | |
| 7 | 24 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 6 | |
| 13 | 4 | |
| 14 | 44 | |
| 15 | 3 | |
| 16 | 127 | |
| 17 | 4 | |
| 18 | 14 | |
| 19 | 3 | |
| 20 | TLC Separation of Some Inorganic Ions Using Nitrilotriacetic Acid-impregnated Plates | 1 |
About Subodh Srivastava
Subodh Srivastava is a scholar working on Computer Vision and Pattern Recognition, Analytical Chemistry and Media Technology, having authored 169 papers that have together received 1.8k indexed citations. Recurring topics across this work include Analytical Chemistry and Chromatography (28 papers), Image and Signal Denoising Methods (25 papers) and AI in cancer detection (18 papers). The work is most often cited by research in Health, Toxicology and Mutagenesis (285 citations), Computer Vision and Pattern Recognition (318 citations) and Analytical Chemistry (141 citations). Subodh Srivastava has collaborated with scholars based in India, United Kingdom and United States. Frequent co-authors include Rajeev Srivastava, Rajesh Kumar Dhanaraj, V. K. Dua, Niraj Pant, D. K. Saxena, Nachiappan Chockalingam, N. Mathur, Y. K. Vijay, Shivani Pandey and Jordan L. Holtzman. Their work appears in journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and The Science of The Total Environment.
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.