Nabarun Bhattacharyya

3.3k total citations
120 papers, 2.4k citations indexed

About

Nabarun Bhattacharyya is a scholar working on Biomedical Engineering, Analytical Chemistry and Nutrition and Dietetics. According to data from OpenAlex, Nabarun Bhattacharyya has authored 120 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Biomedical Engineering, 37 papers in Analytical Chemistry and 32 papers in Nutrition and Dietetics. Recurrent topics in Nabarun Bhattacharyya's work include Advanced Chemical Sensor Technologies (95 papers), Spectroscopy and Chemometric Analyses (35 papers) and Biochemical Analysis and Sensing Techniques (32 papers). Nabarun Bhattacharyya is often cited by papers focused on Advanced Chemical Sensor Technologies (95 papers), Spectroscopy and Chemometric Analyses (35 papers) and Biochemical Analysis and Sensing Techniques (32 papers). Nabarun Bhattacharyya collaborates with scholars based in India, Russia and United Kingdom. Nabarun Bhattacharyya's co-authors include Rajib Bandyopadhyay, Bipan Tudu, Arun Jana, Runu Banerjee Roy, Pradip Tamuly, Sharvari Deshmukh, R.A. Pandey, Manabendra Bhuyan, Arunangshu Ghosh and Devdulal Ghosh and has published in prestigious journals such as SHILAP Revista de lepidopterología, Trends in Food Science & Technology and Atmospheric Environment.

In The Last Decade

Nabarun Bhattacharyya

116 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Nabarun Bhattacharyya India 27 1.8k 647 464 387 359 120 2.4k
Bipan Tudu India 32 2.2k 1.2× 1.2k 1.9× 696 1.5× 437 1.1× 421 1.2× 198 3.5k
Rajib Bandyopadhyay India 35 2.5k 1.4× 1.1k 1.7× 1.2k 2.7× 439 1.1× 484 1.3× 213 4.4k
Arun Jana India 14 906 0.5× 362 0.6× 207 0.4× 187 0.5× 185 0.5× 22 1.1k
Xingyi Huang China 36 1.9k 1.1× 1.4k 2.2× 394 0.8× 302 0.8× 202 0.6× 125 3.8k
S. Benedetti Italy 26 1.2k 0.7× 537 0.8× 220 0.5× 402 1.0× 243 0.7× 69 2.4k
Jiewen Zhao China 42 2.6k 1.5× 2.8k 4.4× 280 0.6× 299 0.8× 258 0.7× 87 4.8k
Jesús Lozano Spain 32 1.7k 1.0× 500 0.8× 677 1.5× 230 0.6× 389 1.1× 119 2.5k
Mahdi Ghasemi‐Varnamkhasti Iran 35 1.8k 1.0× 1.1k 1.7× 596 1.3× 320 0.8× 271 0.8× 102 3.5k
Alisa Rudnitskaya Portugal 41 2.8k 1.6× 555 0.9× 799 1.7× 1.2k 3.1× 785 2.2× 116 4.4k
Zhenbo Wei China 25 890 0.5× 290 0.4× 346 0.7× 284 0.7× 148 0.4× 67 1.4k

Countries citing papers authored by Nabarun Bhattacharyya

Since Specialization
Citations

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

Fields of papers citing papers by Nabarun Bhattacharyya

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Nabarun Bhattacharyya

This figure shows the co-authorship network connecting the top 25 collaborators of Nabarun Bhattacharyya. A scholar is included among the top collaborators of Nabarun Bhattacharyya 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 Nabarun Bhattacharyya. Nabarun Bhattacharyya 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.
Jana, Arun Kumar, et al.. (2023). L-proline enrichment of bread enhances its KFO: Assessment of freshness by electronic nose technology and an ANN prediction model. Applied Food Research. 3(1). 100292–100292. 5 indexed citations
2.
Sharma, Prolay, et al.. (2023). Development of a portable, low-cost QCM sensor-based device for detecting α-pinene in Indian cardamom. Microchemical Journal. 195. 109378–109378. 3 indexed citations
3.
Mukherjee, Subhankar, Souvik Pal, Prasenjit Paria, et al.. (2021). On-spot biosensing device for organophosphate pesticide residue detection in fruits and vegetables. Current Research in Biotechnology. 3. 308–316. 5 indexed citations
4.
Kirsanov, Dmitry, Subhankar Mukherjee, Souvik Pal, et al.. (2021). A Pencil-Drawn Electronic Tongue for Environmental Applications. Sensors. 21(13). 4471–4471. 6 indexed citations
5.
Mukherjee, Subhankar, Souvik Pal, Arnab Halder, et al.. (2021). Sensory development for heavy metal detection: A review on translation from conventional analysis to field-portable sensor. Trends in Food Science & Technology. 109. 674–689. 103 indexed citations
6.
Dhar, Abhishek, Prolay Sharma, Rohit L. Vekariya, et al.. (2020). Development of QCM sensor to detect α-terpinyl acetate in cardamom. Sensors and Actuators A Physical. 319. 112521–112521. 19 indexed citations
7.
Mukherjee, Subhankar, Souvik Pal, Devdulal Ghosh, et al.. (2019). UIISScan 1.1: A Field portable high-throughput platform tool for biomedical and agricultural applications. Journal of Pharmaceutical and Biomedical Analysis. 174. 70–80. 6 indexed citations
8.
Pal, Souvik, Subhankar Mukherjee, & Nabarun Bhattacharyya. (2017). Microorganism and Agricultural Based Biosorbents Towards Removal of Cadmium from Waste-Water: An Overview. Recent Patents on Biotechnology. 11(3). 204–217. 12 indexed citations
9.
Ghosh, Alokesh, et al.. (2014). Generic Handheld E-Nose Platform for Quality Assessment of Agricultural Produces and Biomedical Applications. SHILAP Revista de lepidopterología. 6 indexed citations
10.
Deshmukh, Sharvari, Arun Jana, Rajib Bandyopadhyay, et al.. (2014). Calibration transfer between electronic nose systems for rapid In situ measurement of pulp and paper industry emissions. Analytica Chimica Acta. 841. 58–67. 44 indexed citations
11.
12.
Dey, Tamal K., et al.. (2013). Development of machine vision solution for grading of Tasar silk yarn. 29. 17–20. 3 indexed citations
13.
Bhattacharyya, Nabarun, et al.. (2012). P2.0.10 SnO2 based tea aroma sensors for Electronic Nose. Proceedings IMCS 2012. 1289–1292. 1 indexed citations
14.
15.
Jana, Arun, Rajib Bandyopadhyay, Bipan Tudu, et al.. (2011). Classification of aromatic and non-aromatic rice using electronic nose and artificial neural network. 291–294. 10 indexed citations
16.
Bandyopadhyay, Rajib, et al.. (2011). Electronic Nose Sensor Array Optimization Using Rough Set Theory. AIP conference proceedings. 64–65. 2 indexed citations
17.
Tudu, Bipan, et al.. (2010). Comparison of multivariate preprocessing techniques as applied to electronic tongue based pattern classification for black tea. Analytica Chimica Acta. 675(1). 8–15. 48 indexed citations
18.
Tudu, Bipan, Paramartha Dutta, Arun Jana, et al.. (2009). Classification of Black Tea Taste and Correlation With Tea Taster's Mark Using Voltammetric Electronic Tongue. IEEE Transactions on Instrumentation and Measurement. 59(8). 2230–2239. 95 indexed citations
19.
Tudu, Bipan, Nabarun Bhattacharyya, Arun Jana, Devdulal Ghosh, & Rajib Bandyopadhyay. (2007). Self-Organizing Map Based Classification of Smell Stages of Black Tea Fermentation Process Using Electronic Nose.. Indian International Conference on Artificial Intelligence. 37(3). 1626–1635.
20.
Bhattacharyya, Nabarun, et al.. (1990). Transformation of applied phosphate and its availability in acid soils.. 37(1). 24–30. 1 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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