Anurag Kanase

11 total papers · 856 total citations
10 papers, 659 citations indexed

About

Anurag Kanase is a scholar working on Computational Theory and Mathematics, Pharmacology and Materials Chemistry. According to data from OpenAlex, Anurag Kanase has authored 10 papers receiving a total of 659 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computational Theory and Mathematics, 4 papers in Pharmacology and 3 papers in Materials Chemistry. Recurrent topics in Anurag Kanase's work include Computational Drug Discovery Methods (5 papers), Essential Oils and Antimicrobial Activity (2 papers) and Nanoparticles: synthesis and applications (2 papers). Anurag Kanase is often cited by papers focused on Computational Drug Discovery Methods (5 papers), Essential Oils and Antimicrobial Activity (2 papers) and Nanoparticles: synthesis and applications (2 papers). Anurag Kanase collaborates with scholars based in India, United States and Germany. Anurag Kanase's co-authors include Ajay Vikram Singh, Daniel Rosenkranz, Andreas Luch, Peter Laux, Rishabh Singh, Mohammad Hasan Dad Ansari, Romi Singh Maharjan, Fabian L. Kriegel, Shubham Singh and Katherina Siewert and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACS Applied Materials & Interfaces and Advanced Healthcare Materials.

In The Last Decade

Anurag Kanase

10 papers receiving 645 citations

Author Peers

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

Author Last Decade Papers Cites
Anurag Kanase 206 169 132 116 83 10 659
Daniel Rosenkranz 199 1.0× 180 1.1× 113 0.9× 98 0.8× 70 0.8× 11 587
Romi Singh Maharjan 159 0.8× 132 0.8× 109 0.8× 84 0.7× 54 0.7× 10 587
Rishabh Singh 178 0.9× 149 0.9× 103 0.8× 92 0.8× 66 0.8× 24 571
Zeqing Bao 203 1.0× 194 1.1× 129 1.0× 138 1.2× 66 0.8× 22 578
Kaushik Kumar Bharadwaj 123 0.6× 202 1.2× 158 1.2× 43 0.4× 99 1.2× 14 590
Mian Zu 327 1.6× 235 1.4× 258 2.0× 30 0.3× 97 1.2× 15 791
Mojtaba Falahati 197 1.0× 109 0.6× 236 1.8× 50 0.4× 125 1.5× 29 624
A. P. Subramanian 186 0.9× 114 0.7× 137 1.0× 22 0.2× 159 1.9× 13 600
Chia-Wen Huang 205 1.0× 109 0.6× 276 2.1× 30 0.3× 165 2.0× 12 694
Mei Liu 70 0.3× 72 0.4× 201 1.5× 57 0.5× 118 1.4× 23 632

Countries citing papers authored by Anurag Kanase

Since Specialization
Citations

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

Fields of papers citing papers by Anurag Kanase

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anurag Kanase

This figure shows the co-authorship network connecting the top 25 collaborators of Anurag Kanase. A scholar is included among the top collaborators of Anurag Kanase 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 Anurag Kanase. Anurag Kanase 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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