Mukund Narasimhan

21 total papers · 439 total citations
14 papers, 271 citations indexed

About

Mukund Narasimhan is a scholar working on Artificial Intelligence, Signal Processing and Computational Theory and Mathematics. According to data from OpenAlex, Mukund Narasimhan has authored 14 papers receiving a total of 271 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Artificial Intelligence, 4 papers in Signal Processing and 4 papers in Computational Theory and Mathematics. Recurrent topics in Mukund Narasimhan's work include Natural Language Processing Techniques (4 papers), Embedded Systems Design Techniques (3 papers) and Data Management and Algorithms (3 papers). Mukund Narasimhan is often cited by papers focused on Natural Language Processing Techniques (4 papers), Embedded Systems Design Techniques (3 papers) and Data Management and Algorithms (3 papers). Mukund Narasimhan collaborates with scholars based in United States, India and Singapore. Mukund Narasimhan's co-authors include Paul Viola, Jeff Bilmes, J. Ramanujam, Michael Shilman, Nebojša Jojić, Jeffrey A. Bilmes, Yi Zhang, John Platt, R. Balasubramanian and Rengarajan Amirtharajan and has published in prestigious journals such as ACM Transactions on Design Automation of Electronic Systems, IET Image Processing and Civil War Book Review.

In The Last Decade

Mukund Narasimhan

14 papers receiving 255 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Mukund Narasimhan	159	85	49	40	40	14	271
Yunsheng Bai	183 1.2×	126 1.5×	47 1.0×	27 0.7×	23 0.6×	19	323
Teng Zhang	165 1.0×	122 1.4×	27 0.6×	19 0.5×	25 0.6×	21	252
William A. Martin	165 1.0×	31 0.4×	32 0.7×	79 2.0×	26 0.7×	18	284
M. J. R. Shave	127 0.8×	29 0.3×	42 0.9×	64 1.6×	46 1.1×	22	314
Jo Devriendt	180 1.1×	65 0.8×	54 1.1×	26 0.7×	19 0.5×	10	299
Ekaterina Gonina	160 1.0×	64 0.8×	16 0.3×	14 0.3×	77 1.9×	18	277
Thijs Laarhoven	142 0.9×	119 1.4×	26 0.5×	31 0.8×	22 0.6×	13	234
Universit it Postfach	156 1.0×	44 0.5×	30 0.6×	87 2.2×	18 0.5×	14	238
Shiqing Fan	145 0.9×	83 1.0×	70 1.4×	138 3.5×	46 1.1×	13	290
Ching-pei Lee	144 0.9×	71 0.8×	70 1.4×	26 0.7×	37 0.9×	13	263

Countries citing papers authored by Mukund Narasimhan

Since Specialization

Citations

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

Fields of papers citing papers by Mukund Narasimhan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mukund Narasimhan

This figure shows the co-authorship network connecting the top 25 collaborators of Mukund Narasimhan. A scholar is included among the top collaborators of Mukund Narasimhan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mukund Narasimhan. Mukund Narasimhan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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