Arun Chakraborty

4.3k total citations
211 papers, 2.4k citations indexed

About

Arun Chakraborty is a scholar working on Aerospace Engineering, Global and Planetary Change and Oceanography. According to data from OpenAlex, Arun Chakraborty has authored 211 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 73 papers in Aerospace Engineering, 72 papers in Global and Planetary Change and 64 papers in Oceanography. Recurrent topics in Arun Chakraborty's work include Particle accelerators and beam dynamics (70 papers), Climate variability and models (57 papers) and Magnetic confinement fusion research (54 papers). Arun Chakraborty is often cited by papers focused on Particle accelerators and beam dynamics (70 papers), Climate variability and models (57 papers) and Magnetic confinement fusion research (54 papers). Arun Chakraborty collaborates with scholars based in India, United States and France. Arun Chakraborty's co-authors include J. Kuttippurath, R. K. Srivastava, M. Bandyopadhyay, Rutuparna Panda, Avijit Gangopadhyay, Sourav Sil, Mukesh Sharma, Sudip Jana, Mihir Kumar Purkait and M. Mandal and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Applied Physics.

In The Last Decade

Arun Chakraborty

195 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Arun Chakraborty India 26 908 747 705 458 426 211 2.4k
Daoyi Chen China 38 1.4k 1.6× 633 0.8× 185 0.3× 139 0.3× 894 2.1× 157 5.0k
Xiaofan Yang China 27 776 0.9× 579 0.8× 75 0.1× 96 0.2× 91 0.2× 128 2.3k
Richard Turcotte Canada 26 1.3k 1.4× 822 1.1× 52 0.1× 44 0.1× 197 0.5× 86 2.6k
L.G. Leal France 2 120 0.1× 153 0.2× 136 0.2× 473 1.0× 400 0.9× 2 4.5k
Isao Kudo Japan 25 230 0.3× 182 0.2× 949 1.3× 118 0.3× 250 0.6× 149 1.9k
Yunzhao Li China 21 159 0.2× 73 0.1× 138 0.2× 79 0.2× 447 1.0× 130 1.6k
R. D. Braddock Australia 29 265 0.3× 182 0.2× 120 0.2× 618 1.3× 70 0.2× 128 2.3k
David G. Sloan United States 5 128 0.1× 148 0.2× 133 0.2× 465 1.0× 500 1.2× 10 4.6k
Arden L. Buck United States 7 584 0.6× 470 0.6× 97 0.1× 141 0.3× 143 0.3× 13 1.4k
Bhaskar J. Choudhury United States 42 2.2k 2.4× 3.3k 4.4× 91 0.1× 348 0.8× 416 1.0× 134 6.0k

Countries citing papers authored by Arun Chakraborty

Since Specialization
Citations

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

Fields of papers citing papers by Arun Chakraborty

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Arun Chakraborty

This figure shows the co-authorship network connecting the top 25 collaborators of Arun Chakraborty. A scholar is included among the top collaborators of Arun Chakraborty 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 Arun Chakraborty. Arun Chakraborty 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.
Kuttippurath, J., et al.. (2025). Rapid intensification of the Super Cyclone Amphan: Environmental drivers and its future projections. SHILAP Revista de lepidopterología. 14(1). 27–39.
2.
Bandyopadhyay, M., et al.. (2024). Event driven high speed data acquisition with IEEE 1588 synchronization for long pulse operations of Indian Test Facility for ITER DNB. Fusion Engineering and Design. 204. 114487–114487. 1 indexed citations
3.
4.
Sharma, Mukesh, et al.. (2024). Carbon quantum dots for efficient hydrogen production: A critical review. ChemCatChem. 16(16). 6 indexed citations
5.
Srivastava, R. K., et al.. (2024). Correction: Bias Correction and Trend Analysis of Temperature and Rainfall in Eastern India. Proceedings of the National Academy of Sciences India Section A Physical Sciences. 95(1). 15–15.
6.
Sharma, Sakshi, Abhishek Kumar, & Arun Chakraborty. (2024). Intensification of heatwave conditions during Cyclone Mocha in 2023. Weather. 79(7). 220–223. 4 indexed citations
7.
Chakraborty, Arun, et al.. (2024). Study of Cold Wave and Cold Stress in the Four Metropolitan Cities of India for the Period 1985–2020. 7(2). 83–113. 3 indexed citations
8.
Kuttippurath, J., et al.. (2023). Stressors of primary productivity in the north Indian ocean revealed by satellite, reanalysis and CMIP6 data. Progress In Oceanography. 219. 103164–103164. 8 indexed citations
9.
Chakraborty, Arun, et al.. (2023). Sequential occurrence and development of three tropical cyclones in the Bay of Bengal in 2013. Dynamics of Atmospheres and Oceans. 102. 101363–101363. 8 indexed citations
10.
Chakraborty, Arun, et al.. (2023). Analysis of marine heatwaves over the Bay of Bengal during 1982–2021. Scientific Reports. 13(1). 14235–14235. 8 indexed citations
11.
Gupta, Srimanta, et al.. (2021). Effect of different land use land cover on surface heat budget – A case study from a tropical humid region of India. Remote Sensing Applications Society and Environment. 25. 100675–100675. 4 indexed citations
12.
Kumar, Abhishek, et al.. (2021). Analysis of heat stress and heat wave in the four metropolitan cities of India in recent period. The Science of The Total Environment. 818. 151788–151788. 59 indexed citations
13.
Srivastava, R. K., Rutuparna Panda, & Arun Chakraborty. (2020). Quantification of nitrogen transformation and leaching response to agronomic management for maize crop under rainfed and irrigated condition. Environmental Pollution. 265(Pt A). 114866–114866. 16 indexed citations
14.
Francis, P. A., et al.. (2020). A numerical study on seasonal transport variability of the North Indian Ocean boundary currents using Regional Ocean Modeling System (ROMS). Journal of Operational Oceanography. 15(1). 32–51. 4 indexed citations
15.
Singh, Mahendrajit, et al.. (2020). Conceptual design of Doppler shift spectroscopy diagnostics for INTF. Fusion Engineering and Design. 161. 112005–112005. 1 indexed citations
16.
Raj, Sarath, Saikat Kumar Paul, Arun Chakraborty, & J. Kuttippurath. (2019). Analysis of spatial and temporal variations of surface urban heat island in Kolkata, India using LANDSAT and MODIS data. EGU General Assembly Conference Abstracts. 5854. 2 indexed citations
17.
18.
Chakraborty, Arun & Avijit Gangopadhyay. (2016). Development of a High-Resolution Multiscale Modeling and Prediction System for Bay of Bengal, Part II: An Application to October 2008. Open Journal of Marine Science. 6(1). 125–144. 6 indexed citations
19.
Chakraborty, Arun & Avijit Gangopadhyay. (2016). Development of a High-Resolution Multiscale Modeling and Prediction System for Bay of Bengal, Part I: Climatology-Based Simulations. Open Journal of Marine Science. 6(1). 145–176. 15 indexed citations
20.
Chakraborty, Arun, et al.. (2011). Seasonal variability of heat content and isothermal layer in the Bay of Bengal. 2(3). 63–77. 2 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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