Subhrajit Dey

509 citations
21 papers · 371 · h-index 11

Impact in

Papers in

Subhrajit Dey

21 papers receiving 347 citations

Peers

Subhrajit Dey
Comparison fields: 5 of 88
  • Health Informatics 6
  • Radiology, Nuclear Medicine and Imaging 103
  • Computational Mechanics 73
  • Computer Vision and Pattern Recognition 68
  • Media Technology 29
Replace Abhay Kumar with:
Abhay Kumar India
Emma Regentova United States
Ercan Avşar Türkiye
S. Malarvizhi India
Jing Qin China
Muhammad Amir Pakistan
Meng Zhao China
Tong Chen China
Darian M. Onchiş Romania
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Citations per field
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Citations per year

Countries citing papers authored by Subhrajit Dey

Since Specialization
Citations

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

Fields of papers citing papers by Subhrajit Dey

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Subhrajit Dey, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Subhrajit Dey Line = papers co-authored together Subhrajit Dey links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 21 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200658
2 202246
3 202142
4 202141
5 202230
6 200929
7 202226
8 201021
9 202114
10
A Valve Design Methodology For Improved Reciprocating Compressor Performance
201213
11 202212
12 202210
13 20087
14
Muffler Design for a Refrigerator Compressor
20146
15 20074
16 20113
17 20203
18
Design and Development of Three Phase Permanent Magnet Brushless DC (PM BLDC) Motor for Variable Speed
20122
19 20112
20 20091

About Subhrajit Dey

Subhrajit Dey is a scholar working on Computational Mechanics, Mechanical Engineering, Radiology, Nuclear Medicine and Imaging, Aerospace Engineering and Computer Vision and Pattern Recognition, having authored 21 papers that have together received 371 indexed citations. Recurring topics across this work include COVID-19 diagnosis using AI (4 papers), Combustion and flame dynamics (3 papers), Anomaly Detection Techniques and Applications (3 papers), Refrigeration and Air Conditioning Technologies (3 papers), Building Energy and Comfort Optimization (2 papers), Electric Motor Design and Analysis (2 papers), Heat Transfer Mechanisms (2 papers) and Radiative Heat Transfer Studies (2 papers). The work is most often cited by research in Health Informatics (6 citations), Radiology, Nuclear Medicine and Imaging (103 citations), Computational Mechanics (73 citations), Computer Vision and Pattern Recognition (68 citations) and Media Technology (29 citations). Subhrajit Dey has collaborated with scholars based in India, United States and Australia. Frequent co-authors include Ram Sarkar, Samir Malakar, Rajarshi Roychoudhury, José L. Castillo, Seyedali Mirjalili, Hitesh Mistry, Friedhelm Schwenker, Rishav Pramanik, Ramanathan Muthuganapathy and Vaibhav Bahadur. Their work appears in journals such as Applied Thermal Engineering, Computers in Biology and Medicine, Scientific Reports, International Communications in Heat and Mass Transfer and Journal of Physics D Applied Physics.

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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