Arkaprava Banerjee

29 papers and 530 indexed citations i.

About

Arkaprava Banerjee is a scholar working on Computational Theory and Mathematics, Materials Chemistry and Analytical Chemistry. According to data from OpenAlex, Arkaprava Banerjee has authored 29 papers receiving a total of 530 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computational Theory and Mathematics, 9 papers in Materials Chemistry and 5 papers in Analytical Chemistry. Recurrent topics in Arkaprava Banerjee’s work include Computational Drug Discovery Methods (21 papers), Machine Learning in Materials Science (8 papers) and Spectroscopy and Chemometric Analyses (5 papers). Arkaprava Banerjee is often cited by papers focused on Computational Drug Discovery Methods (21 papers), Machine Learning in Materials Science (8 papers) and Spectroscopy and Chemometric Analyses (5 papers). Arkaprava Banerjee collaborates with scholars based in India, Italy and Poland. Arkaprava Banerjee's co-authors include Kunal Roy, Priyanka De, Mainak Chatterjee, Agnieszka Gajewicz, Supratik Kar, Vinay Kumar, Emilio Benfenati, Edoardo Carnesecchi, Simone Tosi and Paola Gramatica and has published in prestigious journals such as Journal of Hazardous Materials, Scientific Reports and Chemosphere.

In The Last Decade

Co-authorship network of co-authors of Arkaprava Banerjee i

Fields of papers citing papers by Arkaprava Banerjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Countries citing papers authored by Arkaprava Banerjee

Since Specialization
Citations

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

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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2025