Rishabh Singh

24 papers receiving 643 citations

Peers

Rishabh Singh
Comparison fields: 5 of 128
  • Health Informatics 9
  • Computational Theory and Mathematics 93
  • Biomaterials 68
  • Neurology 38
  • Biomedical Engineering 185
Replace Romi Singh Maharjan with:
Romi Singh Maharjan Germany
Anurag Kanase India
Mohammad Hasan Dad Ansari Italy
Runzhi Li China
Faheem Ahmed South Korea
Zhaolei Wang China
Jiahao Wang China
Huiying Zhao China
Yingjie Ma China
Zinan Zhao China
Rishabh Singh relative to Romi Singh Maharjan Germany Romi Singh Maharjan's profile →
Citations per field
00.5×4.8×
Romi Singh Maharjan · 1×
Citations per year

Countries citing papers authored by Rishabh Singh

Since Specialization
Citations

This map shows the geographic impact of Rishabh 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 Rishabh Singh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rishabh Singh more than expected).

Fields of papers citing papers by Rishabh Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rishabh 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 Rishabh Singh. The network helps show where Rishabh Singh may publish in the future.

Co-authors

The 25 scholars most cited alongside Rishabh Singh, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Rishabh Singh Line = papers co-authored together Rishabh Singh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 31 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020248
2 2020132
3 2020116
4 202040
5 202335
6 202222
7 199319
8 201314
9 202012
10 20205
11 20224
12 20243
13 20243
14
Time Series Analysis using a Kernel based Multi-Modal Uncertainty Decomposition Framework
20202
15 20182
16 20232
17
Fungal Flora of Vermicompost and Organic Manure : A case Study of Molecular Diversity of Mucor racemosus using RAPD Analysis
20131
18 20251
19 20241
20 20201

About Rishabh Singh

Rishabh Singh is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Computational Theory and Mathematics, Cardiology and Cardiovascular Medicine and Signal Processing, having authored 31 papers that have together received 667 indexed citations. Recurring topics across this work include Neural Networks and Applications (4 papers), Advanced Neural Network Applications (3 papers), Computational Drug Discovery Methods (3 papers), COVID-19 and Mental Health (2 papers), Biomedical Ethics and Regulation (2 papers), Model Reduction and Neural Networks (2 papers), Nanoparticles: synthesis and applications (2 papers) and CAR-T cell therapy research (2 papers). The work is most often cited by research in Health Informatics (9 citations), Computational Theory and Mathematics (93 citations), Biomaterials (68 citations), Neurology (38 citations) and Biomedical Engineering (185 citations). Rishabh Singh has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Andreas Luch, Anurag Kanase, Peter Laux, Daniel Rosenkranz, Mohammad Hasan Dad Ansari, Romi Singh Maharjan, Fabian L. Kriegel, Katherina Siewert, Ajay Vikram Singh and Blair D. Johnston. Their work appears in journals such as Blood, Journal of Clinical Oncology, IEEE Transactions on Microwave Theory and Techniques, Advanced Healthcare Materials and International Journal of Human Capital and Information Technology Professionals.

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.

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