Nirav Merchant

3.2k total citations
54 papers, 1.0k citations indexed

About

Nirav Merchant is a scholar working on Information Systems and Management, Molecular Biology and Information Systems. According to data from OpenAlex, Nirav Merchant has authored 54 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Information Systems and Management, 11 papers in Molecular Biology and 8 papers in Information Systems. Recurrent topics in Nirav Merchant's work include Scientific Computing and Data Management (15 papers), Distributed and Parallel Computing Systems (6 papers) and Mobile Health and mHealth Applications (6 papers). Nirav Merchant is often cited by papers focused on Scientific Computing and Data Management (15 papers), Distributed and Parallel Computing Systems (6 papers) and Mobile Health and mHealth Applications (6 papers). Nirav Merchant collaborates with scholars based in United States, Australia and Canada. Nirav Merchant's co-authors include Matthew Vaughn, Eric Lyons, Doreen Ware, David Micklos, Stephen A. Goff, Parker B. Antin, Dan Stanzione, Edwin Skidmore, Asheesh K. Singh and Arti Singh and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and The Astrophysical Journal.

In The Last Decade

Nirav Merchant

51 papers receiving 997 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Nirav Merchant United States 15 267 212 189 164 141 54 1.0k
Dirk Eddelbuettel United States 13 305 1.1× 62 0.3× 60 0.3× 51 0.3× 148 1.0× 33 1.9k
Karthik Ram United States 16 139 0.5× 57 0.3× 455 2.4× 403 2.5× 90 0.6× 39 1.2k
Paula Andrea Martinez United States 6 254 1.0× 276 1.3× 195 1.0× 193 1.2× 35 0.2× 15 754
Peter Arzberger United States 17 258 1.0× 40 0.2× 284 1.5× 262 1.6× 233 1.7× 46 1.5k
Daniel Glez‐Peña Spain 19 576 2.2× 163 0.8× 44 0.2× 89 0.5× 123 0.9× 75 1.5k
Miguel Reboiro‐Jato Spain 18 511 1.9× 216 1.0× 38 0.2× 69 0.4× 132 0.9× 72 1.4k
Johannes Köster Germany 17 1.6k 6.0× 368 1.7× 214 1.1× 114 0.7× 264 1.9× 44 2.5k
Fotis Psomopoulos Greece 14 241 0.9× 44 0.2× 199 1.1× 208 1.3× 46 0.3× 72 825
Alex Hardisty United Kingdom 14 258 1.0× 33 0.2× 459 2.4× 378 2.3× 166 1.2× 55 1.1k
Chris Taylor United Kingdom 24 1.8k 6.7× 100 0.5× 183 1.0× 130 0.8× 178 1.3× 71 2.5k

Countries citing papers authored by Nirav Merchant

Since Specialization
Citations

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

Fields of papers citing papers by Nirav Merchant

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nirav Merchant

This figure shows the co-authorship network connecting the top 25 collaborators of Nirav Merchant. A scholar is included among the top collaborators of Nirav Merchant 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 Nirav Merchant. Nirav Merchant is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Joshi, Ameya, Minsu Cho, Aditya Balu, et al.. (2024). Zero‐shot insect detection via weak language supervision. SHILAP Revista de lepidopterología. 7(1). 9 indexed citations
2.
Koushik, Jayanth, Talukder Z. Jubery, Daren S. Mueller, et al.. (2024). InsectNet: Real-time identification of insects using an end-to-end machine learning pipeline. PNAS Nexus. 4(1). pgae575–pgae575. 4 indexed citations
3.
Ganapathysubramanian, Baskar, George Kantor, Nirav Merchant, et al.. (2024). AIIRA: AI Institute for Resilient Agriculture. AI Magazine. 45(1). 94–98. 2 indexed citations
4.
Iyengar, M. Sriram, et al.. (2024). Resilience Informatics for Public Health. Studies in health technology and informatics. 310. 1276–1280. 1 indexed citations
5.
Ganapathysubramanian, Baskar, Arti Singh, Soumyashree Kar, et al.. (2023). Cyber-agricultural systems for crop breeding and sustainable production. Trends in Plant Science. 29(2). 130–149. 31 indexed citations
6.
Strand, R. J., Sean Davey, Dean Lavelle, et al.. (2023). PhytoOracle: Scalable, modular phenomics data processing pipelines. Frontiers in Plant Science. 14. 1112973–1112973. 8 indexed citations
7.
Douglas, Molly, et al.. (2023). Interpretation and Use of Applied/Operational Machine Learning and Artificial Intelligence in Surgery. Surgical Clinics of North America. 103(2). 317–333. 10 indexed citations
8.
Ernst, Kacey C., et al.. (2022). Design and implementation of a health messaging protocol employed for use within a COVID-19 health dissemination platform. Frontiers in Public Health. 10. 942795–942795. 1 indexed citations
9.
Stryeck, Sarah, Konrad Lang, Christoph Hahn, et al.. (2021). A local platform for user-friendly FAIR data management and reproducible analytics. Journal of Biotechnology. 341. 43–50. 4 indexed citations
10.
Guo, Wei, Arti Singh, Tyson L. Swetnam, et al.. (2021). UAS-Based Plant Phenotyping for Research and Breeding Applications. Plant Phenomics. 2021. 9840192–9840192. 80 indexed citations
11.
Swetnam, Tyson L., et al.. (2018). CyVerse: a Ten-year Perspective on Cyberinfrastructure Development, Collaboration, and Community Building. AGU Fall Meeting Abstracts. 2018. 3 indexed citations
12.
Espy, Kimberly Andrews, et al.. (2018). GRAM. ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam). 1–9. 4 indexed citations
13.
Liu, Yang, Saad M. Khan, Juexin Wang, et al.. (2016). PGen: large-scale genomic variations analysis workflow and browser in SoyKB. BMC Bioinformatics. 17(S13). 337–337. 26 indexed citations
14.
Merchant, Nirav, Eric Lyons, Stephen A. Goff, et al.. (2016). The iPlant Collaborative: Cyberinfrastructure for Enabling Data to Discovery for the Life Sciences. PLoS Biology. 14(1). e1002342–e1002342. 219 indexed citations
15.
Bucksch, Alexander, et al.. (2016). Overcoming the Law of the Hidden in Cyberinfrastructures. Trends in Plant Science. 22(2). 117–123. 4 indexed citations
16.
Hingle, Melanie, Tami Turner, Randa Kutob, et al.. (2015). The EPIC Kids Study: a randomized family-focused YMCA-based intervention to prevent type 2 diabetes in at-risk youth. BMC Public Health. 15(1). 1253–1253. 12 indexed citations
17.
Wang, Liya, et al.. (2014). A genome‐wide association study platform built on iPlant cyber‐infrastructure. Concurrency and Computation Practice and Experience. 27(2). 420–432. 4 indexed citations
18.
Kvilekval, Kristian, Д. В. Федоров, Steve Goff, et al.. (2012). Bisque: Advances in Bioimage Databases.. IEEE Data(base) Engineering Bulletin. 35. 56–64. 5 indexed citations
19.
Carpenter, Stephen R., Peter Arzberger, Terry Chapin, et al.. (2009). The Future of Synthesis in Ecology and Environmental Sciences. 38(11). e7–e7. 3 indexed citations
20.
Haynes, Paul A., et al.. (2006). The wildcat toolbox: a set of perl script utilities for use in peptide mass spectral database searching and proteomics experiments.. PubMed. 17(2). 97–102. 7 indexed citations

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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