Prabhat Kumar

880 citations
36 papers · 646 indexed · h-index 12

Prabhat Kumar

32 papers receiving 625 citations

Peers

Prabhat Kumar
Comparison fields: 5 of 91
  • Hardware and Architecture 66
  • Computer Networks and Communications 183
  • Electrical and Electronic Engineering 390
  • Computer Vision and Pattern Recognition 56
  • Artificial Intelligence 80
Replace Kefei Wang with:
Kefei Wang China
Jiang Li China
Michael De Rosa United States
Alan Ford United States
Roy M. Jenevein United States
Zhilei Chai China
V.V. Bapeswara Rao India
Yongfeng Gu United States
George Theodoridis Greece
Prabhat Kumar relative to Kefei Wang China Kefei Wang's profile →
Citations per field
00.5×9.3×
Kefei Wang · 1×
Citations per year

Countries citing papers authored by Prabhat Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Prabhat Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Prabhat Kumar, 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 Prabhat Kumar Line = papers co-authored together Prabhat Kumar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202411
2 20242
3 20242
4 20240
5 20241
6 20244
7 202412
8 20237
9 202311
10 20236
11 20220
12 202116
13 20219
14 20211
15 202119
16
A bibliometric evaluation and analysis on the maturity of scientific research trends on novel coronavirus (COVID-19)
20202
17 20180
18 20121
19 201037
20 19866

About Prabhat Kumar

Prabhat Kumar is a scholar working on Hardware and Architecture, Computer Vision and Pattern Recognition, Computer Networks and Communications, Radiological and Ultrasound Technology and Transportation, having authored 36 papers that have together received 646 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (9 papers), IoT and Edge/Fog Computing (5 papers), Molecular Sensors and Ion Detection (3 papers), Computational Drug Discovery Methods (3 papers), Non-Invasive Vital Sign Monitoring (3 papers), Parallel Computing and Optimization Techniques (3 papers), Advanced Data Storage Technologies (2 papers) and Photonic and Optical Devices (2 papers). The work is most often cited by research in Hardware and Architecture (66 citations), Computer Networks and Communications (183 citations), Electrical and Electronic Engineering (390 citations), Computer Vision and Pattern Recognition (56 citations) and Artificial Intelligence (80 citations). Prabhat Kumar has collaborated with scholars based in India, United States and South Korea. Frequent co-authors include Alok Choudhary, Yan Pan, John Kim, Gokhan Memik, Yu Zhang, Yu Zhang, Saripella Srikrishna, Vinod P. Singh, Ananya Srivastava and Gautam Kumar. Their work appears in journals such as Journal of Molecular Graphics and Modelling, ACS Chemical Neuroscience, ACM SIGCOMM Computer Communication Review, SAR and QSAR in environmental research and International Journal of Biological Macromolecules.

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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