Saptarshi Kar

809 total citations
41 papers, 641 citations indexed

About

Saptarshi Kar is a scholar working on Polymers and Plastics, Biomedical Engineering and Physiology. According to data from OpenAlex, Saptarshi Kar has authored 41 papers receiving a total of 641 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Polymers and Plastics, 10 papers in Biomedical Engineering and 9 papers in Physiology. Recurrent topics in Saptarshi Kar's work include Nitric Oxide and Endothelin Effects (9 papers), Polymer Nanocomposites and Properties (8 papers) and Eicosanoids and Hypertension Pharmacology (6 papers). Saptarshi Kar is often cited by papers focused on Nitric Oxide and Endothelin Effects (9 papers), Polymer Nanocomposites and Properties (8 papers) and Eicosanoids and Hypertension Pharmacology (6 papers). Saptarshi Kar collaborates with scholars based in United States, Australia and India. Saptarshi Kar's co-authors include Mahendra Kavdia, Xiao Dong Chen, David W. Smith, Bruce S. Gardiner, Rabindra Mukhopadhyay, Roger G. Evans, Jennifer P. Ngo, Farzad Seidi, Mohammad Reza Saeb and Hanieh Shokrani and has published in prestigious journals such as PLoS ONE, Scientific Reports and The FASEB Journal.

In The Last Decade

Saptarshi Kar

37 papers receiving 633 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Saptarshi Kar United States 18 142 122 101 74 70 41 641
Feijie Wang China 19 206 1.5× 125 1.0× 237 2.3× 48 0.6× 23 0.3× 53 945
Yuting Sun China 18 230 1.6× 52 0.4× 96 1.0× 86 1.2× 42 0.6× 69 1.0k
Zisen Zhang China 17 94 0.7× 77 0.6× 132 1.3× 39 0.5× 28 0.4× 35 735
Haiwei Liu China 15 225 1.6× 99 0.8× 31 0.3× 57 0.8× 37 0.5× 67 998
Yajuan Xie China 15 292 2.1× 30 0.2× 122 1.2× 108 1.5× 63 0.9× 35 915
Siqian Wang China 16 112 0.8× 145 1.2× 138 1.4× 61 0.8× 21 0.3× 52 653
Jun Gu China 19 229 1.6× 51 0.4× 166 1.6× 71 1.0× 11 0.2× 64 946
Shujie Yan China 16 267 1.9× 36 0.3× 143 1.4× 30 0.4× 16 0.2× 70 657
Cheng‐Hung Lee Taiwan 20 209 1.5× 69 0.6× 415 4.1× 61 0.8× 17 0.2× 99 1.5k

Countries citing papers authored by Saptarshi Kar

Since Specialization
Citations

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

Fields of papers citing papers by Saptarshi Kar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Saptarshi Kar

This figure shows the co-authorship network connecting the top 25 collaborators of Saptarshi Kar. A scholar is included among the top collaborators of Saptarshi Kar 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 Saptarshi Kar. Saptarshi Kar 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.
Hadavimoghaddam, Fahimeh, Saeid Atashrouz, Saptarshi Kar, et al.. (2025). Innovative mathematical correlations for estimating mono-nanofluids' density: Insights from white-box machine learning. Results in Physics. 73. 108248–108248.
2.
Mohammadi, Mohammad-Reza, et al.. (2025). Modeling residue formation from crude oil oxidation using tree-based machine learning approaches. Scientific Reports. 15(1). 26264–26264.
3.
Kashkooli, Farshad Moradi, et al.. (2025). Mechanical Forces in Tumor Growth and Treatment: Perspectives From Biology, Physics, Engineering, and Mathematical Modeling. PubMed. 17(2). e70000–e70000. 2 indexed citations
4.
Kar, Saptarshi, et al.. (2024). Computational modeling of neuronal nitric oxide synthase biochemical pathway: A mechanistic analysis of tetrahydrobiopterin and oxidative stress. Free Radical Biology and Medicine. 222. 625–637. 3 indexed citations
5.
Shokrani, Hanieh, Farzad Seidi, Saptarshi Kar, et al.. (2023). Polysaccharide‐based biomaterials in a journey from 3D to 4D printing. Bioengineering & Translational Medicine. 8(4). e10503–e10503. 29 indexed citations
6.
Shahvandi, Mohammad Kiani, et al.. (2023). A comparative study between conventional chemotherapy and photothermal activated nano-sized targeted drug delivery to solid tumor. Computers in Biology and Medicine. 166. 107574–107574. 31 indexed citations
7.
Shokrani, Hanieh, S. Mohammad Sajadi, Mohsen Khodadadi Yazdi, et al.. (2022). Polysaccharide-based nanocomposites for biomedical applications: a critical review. Nanoscale Horizons. 7(10). 1136–1160. 46 indexed citations
8.
Shokrani, Hanieh, Maryam Jouyandeh, Farzad Seidi, et al.. (2022). Green Polymer Nanocomposites for Skin Tissue Engineering. ACS Applied Bio Materials. 5(5). 2107–2121. 45 indexed citations
9.
Kar, Saptarshi, et al.. (2021). How does ascorbate improve endothelial dysfunction? - A computational analysis. Free Radical Biology and Medicine. 165. 111–126. 10 indexed citations
10.
11.
Lee, Chang Joon, Bruce S. Gardiner, Jennifer P. Ngo, et al.. (2017). Accounting for oxygen in the renal cortex: a computational study of factors that predispose the cortex to hypoxia. American Journal of Physiology-Renal Physiology. 313(2). F218–F236. 28 indexed citations
12.
Lee, Chang Joon, Jennifer P. Ngo, Saptarshi Kar, et al.. (2017). A pseudo-three-dimensional model for quantification of oxygen diffusion from preglomerular arteries to renal tissue and renal venous blood. American Journal of Physiology-Renal Physiology. 313(2). F237–F253. 20 indexed citations
13.
Ngo, Jennifer P., Saptarshi Kar, Michelle M. Kett, et al.. (2014). Vascular geometry and oxygen diffusion in the vicinity of artery-vein pairs in the kidney. American Journal of Physiology-Renal Physiology. 307(10). F1111–F1122. 26 indexed citations
14.
Kar, Saptarshi & Mahendra Kavdia. (2013). Endothelial NO and O2− production rates differentially regulate oxidative, nitroxidative, and nitrosative stress in the microcirculation. Free Radical Biology and Medicine. 63. 161–174. 25 indexed citations
15.
Kar, Saptarshi, et al.. (2012). Impact of SOD in eNOS uncoupling: a two-edged sword between hydrogen peroxide and peroxynitrite. Free Radical Research. 46(12). 1496–1513. 24 indexed citations
16.
Kar, Saptarshi & Mahendra Kavdia. (2012). Local Oxidative and Nitrosative Stress Increases in the Microcirculation during Leukocytes-Endothelial Cell Interactions. PLoS ONE. 7(6). e38912–e38912. 9 indexed citations
17.
Kar, Saptarshi, et al.. (2011). Montmorillonite clay nanocomposites based on vinyl pyridine‐styrene‐butadiene terpolymer (VPR)/acrylonitrile‐butadiene rubber (NBR) blend. Polymer Engineering and Science. 51(8). 1675–1681. 3 indexed citations
18.
Kar, Saptarshi & Mahendra Kavdia. (2011). Modeling of biopterin-dependent pathways of eNOS for nitric oxide and superoxide production. Free Radical Biology and Medicine. 51(7). 1411–1427. 33 indexed citations
19.
20.
Kar, Saptarshi, et al.. (2010). Effect of Ozone, Thermo, and Thermo-oxidative Aging on the Physical Property of Styrene Butadiene Rubber-Organoclay Nanocomposites. Journal of Elastomers & Plastics. 42(5). 443–452. 12 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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