Sunil Kumar Prabhakar

1.4k citations
88 papers · 775 · h-index 15

Impact in

Papers in

Sunil Kumar Prabhakar

80 papers receiving 593 citations

Peers

Sunil Kumar Prabhakar
Comparison fields: 5 of 94
  • Signal Processing 251
  • Cognitive Neuroscience 403
  • Artificial Intelligence 281
  • Health Informatics 10
  • Health Information Management 29
Replace Palani Thanaraj Krishnan with:
Palani Thanaraj Krishnan India
Mohammad-Parsa Hosseini United States
Mahmut Hekim Türkiye
Gökhan Altan Türkiye
Hisham Daoud United States
Binish Fatimah India
Mohammad Zavid Parvez Bangladesh
Rayyan Azam Khan Canada
Fardin Abdali-Mohammadi Iran
J. S. Sahambi India
Sunil Kumar Prabhakar relative to Palani Thanaraj Krishnan India Palani Thanaraj Krishnan's profile →
Citations per field
00.5×10×15×20×23.5×
Palani Thanaraj Krishnan · 1×
Citations per year

Countries citing papers authored by Sunil Kumar Prabhakar

Since Specialization
Citations

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

Fields of papers citing papers by Sunil Kumar Prabhakar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 12 scholars most cited alongside Sunil Kumar Prabhakar, 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 Sunil Kumar Prabhakar Line = papers co-authored together Sunil Kumar Prabhakar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202064
2 202243
3 202139
4 202033
5 201927
6 202027
7 202024
8 201720
9 202019
10 202218
11 201717
12 202216
13 201716
14 201715
15 201615
16 201714
17 202213
18 201612
19 201712
20 202012

About Sunil Kumar Prabhakar

Sunil Kumar Prabhakar is a scholar working on Cognitive Neuroscience, Signal Processing, Artificial Intelligence, Molecular Biology and Cardiology and Cardiovascular Medicine, having authored 88 papers that have together received 775 indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (61 papers), Blind Source Separation Techniques (41 papers), Neural Networks and Applications (24 papers), Fractal and DNA sequence analysis (10 papers), ECG Monitoring and Analysis (9 papers), Machine Learning in Bioinformatics (8 papers), AI in cancer detection (8 papers) and Gene expression and cancer classification (7 papers). The work is most often cited by research in Signal Processing (251 citations), Cognitive Neuroscience (403 citations), Artificial Intelligence (281 citations), Health Informatics (10 citations) and Health Information Management (29 citations). Sunil Kumar Prabhakar has collaborated with scholars based in South Korea, India and Nigeria. Frequent co-authors include Harikumar Rajaguru, Seong‐Whan Lee, Dong-Ok Won, Sun‐Hee Kim, In Cheol Jeong, Deepa Kumari, Chulho Kim, Semin Ryu, Jae Jun Lee and Jong‐Hee Sohn. Their work appears in journals such as IEEE Access, Expert Systems with Applications, Computational Intelligence and Neuroscience, BioMed Research International and Heliyon.

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.

Explore authors with similar magnitude of impact