Suparna Biswas

153 total papers · 1.4k total citations
69 papers, 767 citations indexed

About

Suparna Biswas is a scholar working on Computer Networks and Communications, Biomedical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Suparna Biswas has authored 69 papers receiving a total of 767 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Computer Networks and Communications, 27 papers in Biomedical Engineering and 25 papers in Computer Vision and Pattern Recognition. Recurrent topics in Suparna Biswas's work include Context-Aware Activity Recognition Systems (21 papers), IoT and Edge/Fog Computing (19 papers) and Wireless Body Area Networks (18 papers). Suparna Biswas is often cited by papers focused on Context-Aware Activity Recognition Systems (21 papers), IoT and Edge/Fog Computing (19 papers) and Wireless Body Area Networks (18 papers). Suparna Biswas collaborates with scholars based in India, United Kingdom and Iran. Suparna Biswas's co-authors include Dipanwita Thakur, Sarmistha Neogy, Chandreyee Chowdhury, Samiran Chattopadhyay, Edmond S. L. Ho, Sushanta Karmakar, Manju Khari, Vimal Shanmuganathan, R. Gupta and Nauman Aslam and has published in prestigious journals such as IEEE Access, IEEE Sensors Journal and Journal of Network and Computer Applications.

In The Last Decade

Suparna Biswas

65 papers receiving 722 citations

Author Peers

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

Author Last Decade Papers Cites
Suparna Biswas 348 248 186 151 132 69 767
Javier Medina-Quero 238 0.7× 519 2.1× 142 0.8× 210 1.4× 175 1.3× 65 845
S. Padmavathi 178 0.5× 242 1.0× 131 0.7× 184 1.2× 95 0.7× 47 675
Sira Yongchareon 159 0.5× 163 0.7× 182 1.0× 163 1.1× 286 2.2× 53 845
P. Prabu 121 0.3× 174 0.7× 76 0.4× 157 1.0× 83 0.6× 44 686
Shuai Zhang 176 0.5× 410 1.7× 67 0.4× 226 1.5× 109 0.8× 84 808
M.R. Ito 195 0.6× 80 0.3× 144 0.8× 150 1.0× 88 0.7× 99 903
Shuo-Tsung Chen 186 0.5× 230 0.9× 63 0.3× 58 0.4× 75 0.6× 67 672
Caroline Langensiepen 126 0.4× 434 1.8× 101 0.5× 173 1.1× 132 1.0× 65 823
Juan Manuel García‐Chamizo 132 0.4× 124 0.5× 130 0.7× 140 0.9× 166 1.3× 68 811
Jie Chen 138 0.4× 230 0.9× 76 0.4× 105 0.7× 34 0.3× 43 796

Countries citing papers authored by Suparna Biswas

Since Specialization
Citations

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

Fields of papers citing papers by Suparna Biswas

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suparna Biswas

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