Kapil Gadkar

66 total papers · 2.9k total citations
37 papers, 1.5k citations indexed

About

Kapil Gadkar is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Control and Systems Engineering. According to data from OpenAlex, Kapil Gadkar has authored 37 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 13 papers in Radiology, Nuclear Medicine and Imaging and 8 papers in Control and Systems Engineering. Recurrent topics in Kapil Gadkar's work include Monoclonal and Polyclonal Antibodies Research (13 papers), Microbial Metabolic Engineering and Bioproduction (7 papers) and Computational Drug Discovery Methods (7 papers). Kapil Gadkar is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (13 papers), Microbial Metabolic Engineering and Bioproduction (7 papers) and Computational Drug Discovery Methods (7 papers). Kapil Gadkar collaborates with scholars based in United States, Switzerland and Netherlands. Kapil Gadkar's co-authors include Francis J. Doyle, Saroja Ramanujan, Rudiyanto Gunawan, Jeffrey D. Varner, Daniel C. Kirouac, Iraj Hosseini, Radhakrishnan Mahadevan, Jeremy S. Edwards, Mark S. Dennis and Jessica A. Couch and has published in prestigious journals such as Automatica, Genome Research and Annals of the New York Academy of Sciences.

In The Last Decade

Kapil Gadkar

36 papers receiving 1.4k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Kapil Gadkar 822 396 286 206 168 37 1.5k
Jeffrey D. Varner 1.5k 1.8× 74 0.2× 167 0.6× 139 0.7× 267 1.6× 69 2.1k
Travis S. Johnson 711 0.9× 114 0.3× 195 0.7× 139 0.7× 44 0.3× 52 1.3k
Vinay Varadan 726 0.9× 458 1.2× 454 1.6× 151 0.7× 85 0.5× 69 1.8k
Petr Vaňhara 413 0.5× 94 0.2× 297 1.0× 188 0.9× 120 0.7× 52 1.5k
Luca Marchetti 673 0.8× 119 0.3× 347 1.2× 149 0.7× 142 0.8× 88 1.6k
Xinyi Wu 1.3k 1.6× 84 0.2× 421 1.5× 222 1.1× 39 0.2× 72 2.0k
Martin Peifer 1.0k 1.3× 103 0.3× 894 3.1× 124 0.6× 51 0.3× 54 2.2k
Yue Cui 869 1.1× 152 0.4× 410 1.4× 281 1.4× 30 0.2× 59 1.8k
Xiaobo Zhou 700 0.9× 256 0.6× 361 1.3× 124 0.6× 99 0.6× 50 1.6k
Ulrike Korf 1.7k 2.1× 287 0.7× 280 1.0× 74 0.4× 171 1.0× 63 2.2k

Countries citing papers authored by Kapil Gadkar

Since Specialization
Citations

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

Fields of papers citing papers by Kapil Gadkar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kapil Gadkar

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

All Works

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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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