Raj Bhatnagar

606 citations
55 papers · 380 · h-index 11

Impact in

Papers in

    • Advanced Clustering Algorithms Research 7
    • AI-based Problem Solving and Planning 5
    • Bayesian Modeling and Causal Inference 5
    • Data Mining Algorithms and Applications 15

Raj Bhatnagar

51 papers receiving 353 citations

Peers

Raj Bhatnagar
Comparison fields: 5 of 81
  • Artificial Intelligence 164
  • Signal Processing 48
  • Computational Theory and Mathematics 61
  • Information Systems 71
  • Computer Networks and Communications 68
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Citations per field
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Citations per year

Countries citing papers authored by Raj Bhatnagar

Since Specialization
Citations

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

Fields of papers citing papers by Raj Bhatnagar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 198642
2 201132
3 201230
4 201629
5 200228
6 201018
7
Agents for Integrating Distributed Data for Complex Computations
200616
8 200714
9 199713
10 200812
11 201211
12
New Algorithm for Clustering Distributed Data Using k-Means
201510
13 20217
14 20097
15
Authorship Attribution By Consensus Among Multiple Features.
20186
16 20096
17
Similarity measures in formal concept analysis.
20106
18 20226
19 20156
20 19976

About Raj Bhatnagar

Raj Bhatnagar is a scholar working on Artificial Intelligence, Information Systems, Molecular Biology, Signal Processing and Computational Theory and Mathematics, having authored 55 papers that have together received 380 indexed citations. Recurring topics across this work include Data Mining Algorithms and Applications (15 papers), Data Management and Algorithms (14 papers), Bioinformatics and Genomic Networks (10 papers), Gene expression and cancer classification (9 papers), Rough Sets and Fuzzy Logic (8 papers), Advanced Clustering Algorithms Research (7 papers), AI-based Problem Solving and Planning (5 papers) and Bayesian Modeling and Causal Inference (5 papers). The work is most often cited by research in Artificial Intelligence (164 citations), Signal Processing (48 citations), Computational Theory and Mathematics (61 citations), Information Systems (71 citations) and Computer Networks and Communications (68 citations). Raj Bhatnagar has collaborated with scholars based in United States, India and Italy. Frequent co-authors include Laveen N. Kanal, Zhen Hu, Ahmed M. Khedr, Hazem Elzarka, Debaditya Chakraborty, Sriram Srinivasan, Shengchang Su, Long Lu, Daniel J. Hassett and Minlu Zhang. Their work appears in journals such as Statistical Analysis and Data Mining The ASA Data Science Journal, IEEE Transactions on Pattern Analysis and Machine Intelligence, PLoS ONE, Sustainable Cities and Society and Pattern Recognition Letters.

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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