Rishabh Singh

22 papers receiving 672 citations

Peers

Rishabh Singh
Comparison fields: 5 of 103
  • Drug Discovery 4
  • Biomaterials 138
  • Health Informatics 25
  • Computational Theory and Mathematics 87
  • Neurology 38
Replace Daniel Rosenkranz with:
Daniel Rosenkranz Germany
Anurag Kanase India
Mohammad Hasan Dad Ansari Italy
Romi Singh Maharjan Germany
Runzhi Li China
Fabian L. Kriegel Germany
Cheng Chen China
Aytug Kara Spain
Brayan J. Anaya Spain
Baris Öngoren Spain
Rishabh Singh relative to Daniel Rosenkranz Germany Daniel Rosenkranz's profile →
Citations per field
00.5×2×3×3.8×
Daniel Rosenkranz · 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 25 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2020261
2 2020136
3 2020125
4 202043
5 202341
6 202222
7 199318
8 201315
9 202013
10 20205
11 20225
12 20182
13
Time Series Analysis using a Kernel based Multi-Modal Uncertainty Decomposition Framework
20202
14 20232
15 20242
16 20252
17
Fungal Flora of Vermicompost and Organic Manure : A case Study of Molecular Diversity of Mucor racemosus using RAPD Analysis
20131
18 20191
19
Towards a Kernel based Physical Interpretation of Model Uncertainty.
20201
20 20201

About Rishabh Singh

Rishabh Singh is a scholar working on Health Information Management, Artificial Intelligence, Cancer Research, Materials Chemistry and Internal Medicine, having authored 25 papers that have together received 700 indexed citations. Recurring topics across this work include Gaussian Processes and Bayesian Inference (2 papers), Artificial Intelligence in Healthcare (2 papers), Nanoparticles: synthesis and applications (2 papers), Machine Learning in Materials Science (2 papers), Advanced Neural Network Applications (2 papers), Lung Cancer Treatments and Mutations (1 paper), Composting and Vermicomposting Techniques (1 paper) and Sensorless Control of Electric Motors (1 paper). The work is most often cited by research in Drug Discovery (4 citations), Biomaterials (138 citations), Health Informatics (25 citations), Computational Theory and Mathematics (87 citations) and Neurology (38 citations). Rishabh Singh has collaborated with scholars based in United States, India and Germany. Frequent co-authors include Anurag Kanase, Peter Laux, Daniel Rosenkranz, Andreas Luch, Mohammad Hasan Dad Ansari, Romi Singh Maharjan, Fabian L. Kriegel, Blair D. Johnston, Ajay Vikram Singh and Shubham Pratap Singh. Their work appears in journals such as ACS Applied Materials & Interfaces, International Journal of Human Capital and Information Technology Professionals, Thrombosis Research, IEEE Transactions on Microwave Theory and Techniques and Journal of Clinical Oncology.

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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