Subhash Kak

4.7k citations
188 papers · 1.6k · h-index 19

Impact in

Papers in

Subhash Kak

170 papers receiving 1.4k citations

Peers

Subhash Kak
Comparison fields: 5 of 140
  • Artificial Intelligence 792
  • Theoretical Computer Science 21
  • Computer Vision and Pattern Recognition 286
  • Computational Theory and Mathematics 178
  • Signal Processing 99
Replace Oren Patashnik with:
Oren Patashnik United States
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M. Shub United States
James F. Peters Canada
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W.J. Worlton United States
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Citations per field
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Citations per year

Countries citing papers authored by Subhash Kak

Since Specialization
Citations

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

Fields of papers citing papers by Subhash Kak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 188 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1995153
2 199983
3 200671
4 200965
5 197060
6 201046
7 200741
8 200733
9 200229
10 202027
11 199627
12 197727
13 199523
14 201523
15 199923
16 200922
17 200919
18 199918
19 199418
20 199318

About Subhash Kak

Subhash Kak is a scholar working on Artificial Intelligence, Atomic and Molecular Physics, and Optics, Computer Vision and Pattern Recognition, Computational Theory and Mathematics and Statistical and Nonlinear Physics, having authored 188 papers that have together received 1.6k indexed citations. Recurring topics across this work include Quantum Mechanics and Applications (33 papers), Quantum Computing Algorithms and Architecture (25 papers), Neural Networks and Applications (25 papers), Quantum Information and Cryptography (23 papers), Chaos-based Image/Signal Encryption (22 papers), Computability, Logic, AI Algorithms (18 papers), Historical Astronomy and Related Studies (11 papers) and Neural dynamics and brain function (9 papers). The work is most often cited by research in Artificial Intelligence (792 citations), Theoretical Computer Science (21 citations), Computer Vision and Pattern Recognition (286 citations), Computational Theory and Mathematics (178 citations) and Signal Processing (99 citations). Subhash Kak has collaborated with scholars based in United States, India and Australia. Frequent co-authors include Abhishek Parakh, Yuhua Chen, N. Jayant, Pramode K. Verma, M. Kafatos, Anindya Chatterjee, Georg Feuerstein, Karl H. Pribram, Deepak Chopra and J.L. Aravena. Their work appears in journals such as Information Sciences, Electronics Letters, Mankind Quarterly, Proceedings of the IEEE and Scientific Reports.

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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