M. Punithavalli

126 total papers · 691 total citations
70 papers, 369 citations indexed

About

M. Punithavalli is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, M. Punithavalli has authored 70 papers receiving a total of 369 indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Artificial Intelligence, 21 papers in Information Systems and 18 papers in Computer Vision and Pattern Recognition. Recurrent topics in M. Punithavalli's work include Data Mining Algorithms and Applications (14 papers), Advanced Clustering Algorithms Research (12 papers) and Face and Expression Recognition (9 papers). M. Punithavalli is often cited by papers focused on Data Mining Algorithms and Applications (14 papers), Advanced Clustering Algorithms Research (12 papers) and Face and Expression Recognition (9 papers). M. Punithavalli collaborates with scholars based in India and Ireland. M. Punithavalli's co-authors include S. Punitha, K. Anandakumar, Amar Nath Sharma, Uma Rani, K. Maheswari, Ramapurath S. Jayasree, S. Vijayalakshmi, Sri Ramakrishna, V. Kavitha and K. Thangadurai and has published in prestigious journals such as SHILAP Revista de lepidopterología, Multimedia Tools and Applications and Rice Science.

In The Last Decade

M. Punithavalli

59 papers receiving 320 citations

Author Peers

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

Author						Papers	Cites
M. Punithavalli	139	96	76	58	55	70	369
Giovanni Guzmán	55 0.4×	43 0.4×	123 1.6×	45 0.8×	20 0.4×	60	384
Ioannis Karydis	65 0.5×	32 0.3×	85 1.1×	99 1.7×	8 0.1×	44	333
Valliappan Raman	74 0.5×	107 1.1×	29 0.4×	128 2.2×	24 0.4×	49	346
Wenlong Yi	70 0.5×	139 1.4×	86 1.1×	46 0.8×	27 0.5×	45	395
Krishna Chandramouli	95 0.7×	92 1.0×	72 0.9×	146 2.5×	11 0.2×	41	432
Dinesh Kumar Anguraj	106 0.8×	91 0.9×	21 0.3×	52 0.9×	13 0.2×	69	359
Amit Verma	55 0.4×	35 0.4×	35 0.5×	127 2.2×	19 0.3×	44	344
Haoliang Qi	186 1.3×	105 1.1×	72 0.9×	30 0.5×	75 1.4×	56	381
Anamika Chauhan	91 0.7×	146 1.5×	32 0.4×	21 0.4×	19 0.3×	47	410
Héctor Migallón	74 0.5×	12 0.1×	73 1.0×	89 1.5×	15 0.3×	52	354

Countries citing papers authored by M. Punithavalli

Since Specialization

Citations

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

Fields of papers citing papers by M. Punithavalli

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Punithavalli

This figure shows the co-authorship network connecting the top 25 collaborators of M. Punithavalli. A scholar is included among the top collaborators of M. Punithavalli 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 M. Punithavalli. M. Punithavalli 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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