Ajay Vikram Singh
- Biomedical Engineering
- Materials Chemistry
- Molecular Biology
- Computational Theory and Mathematics top 10%
- Biomaterials
- Co-authors
- Peter LauxAndreas LuchShubham SinghSarada Prasad DakuaVaisali ChandrasekarAshok Kumar DatusaliaNeha GuptaSunil Choudhary
- Topics
- Computational Drug Discovery Methods (6 papers)Bone Tissue Engineering Materials (1 paper)Laser-Ablation Synthesis of Nanoparticles (1 paper)
- Journals
- SHILAP Revista de lepidopterologíaBiomedicine & PharmacotherapyArchives of Toxicology
- Partner nations
- GermanyIndiaUnited States
In The Last Decade
Ajay Vikram Singh
9 papers receiving 350 citations
Hit Papers
Peers
Comparison fields: 5 of 111
- Biomedical Engineering 82
- Materials Chemistry 72
- Molecular Biology 71
- Computational Theory and Mathematics 65
- Biomaterials 34
Countries citing papers authored by Ajay Vikram Singh
This map shows the geographic impact of Ajay Vikram Singh'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 Ajay Vikram Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ajay Vikram Singh more than expected).
Fields of papers citing papers by Ajay Vikram Singh
This network shows the impact of papers produced by Ajay Vikram Singh. 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 Ajay Vikram Singh. The network helps show where Ajay Vikram Singh may publish in the future.
Co-authorship network of co-authors of Ajay Vikram Singh
This figure shows the co-authorship network connecting the top 25 collaborators of Ajay Vikram Singh. A scholar is included among the top collaborators of Ajay Vikram Singh 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 Ajay Vikram Singh. Ajay Vikram Singh 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 | 2 | |
| 3 | 17 | |
| 4 | 50 | |
| 5 | 18 | |
| 6 | 88 | |
| 7 | Artificial intelligence and machine learning disciplines with the potential to improve the nanotoxicology and nanomedicine fields: a comprehensive reviewbreakdown → | 100 |
| 8 | 55 | |
| 9 | 34 | |
| 10 | 1 |
About Ajay Vikram Singh
Ajay Vikram Singh is a scholar working on Computational Theory and Mathematics, Sensory Systems and Biophysics, having authored 10 papers that have together received 365 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Bone Tissue Engineering Materials (1 paper) and Laser-Ablation Synthesis of Nanoparticles (1 paper). The work is most often cited by research in Health Informatics (11 citations), Computational Theory and Mathematics (65 citations) and Health Information Management (13 citations). Ajay Vikram Singh has collaborated with scholars based in Germany, India and United States. Frequent co-authors include Peter Laux, Andreas Luch, Shubham Singh, Sarada Prasad Dakua, Vaisali Chandrasekar, Ashok Kumar Datusalia, Neha Gupta, Sunil Choudhary, Shahab Uddin and Kirti S. Prabhu. Their work appears in journals such as SHILAP Revista de lepidopterología, Biomedicine & Pharmacotherapy and Archives of Toxicology.
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.