Manoj Prabhakaran

5.0k citations
37 papers · 720 · h-index 14

Impact in

Papers in

Manoj Prabhakaran

34 papers receiving 679 citations

Peers

Manoj Prabhakaran
Comparison fields: 5 of 61
  • Artificial Intelligence 619
  • Computational Theory and Mathematics 250
  • Information Systems 170
  • Computer Networks and Communications 124
  • Hardware and Architecture 34
Replace Carmit Hazay with:
Carmit Hazay Israel
Peter Gemmell United States
Gil Segev Israel
Nicolas Gama France
Krzysztof Pietrzak Austria
Daniel Wichs United States
Agostino Dovier Italy
Peter Rindal United States
Benjamin Rossman United States
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Citations per field
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Citations per year

Countries citing papers authored by Manoj Prabhakaran

Since Specialization
Citations

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

Fields of papers citing papers by Manoj Prabhakaran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2014199
2 2005149
3 200342
4 200441
5 200435
6 200231
7 201431
8 201426
9 202121
10 201020
11 200616
12 201616
13 200515
14 201414
15 20209
16 20108
17 20076
18 20126
19 20105
20 20175

About Manoj Prabhakaran

Manoj Prabhakaran is a scholar working on Artificial Intelligence, Computational Theory and Mathematics, Computer Networks and Communications, Electrical and Electronic Engineering and Molecular Biology, having authored 37 papers that have together received 720 indexed citations. Recurring topics across this work include Cryptography and Data Security (25 papers), Complexity and Algorithms in Graphs (12 papers), Cryptographic Implementations and Security (9 papers), Privacy-Preserving Technologies in Data (7 papers), semigroups and automata theory (3 papers), Blockchain Technology Applications and Security (3 papers), Algorithms and Data Compression (3 papers) and Security in Wireless Sensor Networks (3 papers). The work is most often cited by research in Artificial Intelligence (619 citations), Computational Theory and Mathematics (250 citations), Information Systems (170 citations), Computer Networks and Communications (124 citations) and Hardware and Architecture (34 citations). Manoj Prabhakaran has collaborated with scholars based in United States, India and Israel. Frequent co-authors include Carl A. Gunter, Muhammad Naveed, Arun Sahai, Amit Sahai, Rina Panigrahy‎, Abhi Shelat, Moses Charikar, Eric Lehman, D. Liu and Vinod M. Prabhakaran. Their work appears in journals such as IEEE Transactions on Information Theory, Journal of Cryptology, ACM Transactions on Information and System Security, Phytotherapy Research and Lecture notes in computer science.

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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