Arnab Kumar Mondal

57 total papers · 413 total citations
19 papers, 124 citations indexed

About

Arnab Kumar Mondal is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Molecular Biology. According to data from OpenAlex, Arnab Kumar Mondal has authored 19 papers receiving a total of 124 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 3 papers in Molecular Biology. Recurrent topics in Arnab Kumar Mondal's work include Anomaly Detection Techniques and Applications (2 papers), EEG and Brain-Computer Interfaces (2 papers) and Handwritten Text Recognition Techniques (2 papers). Arnab Kumar Mondal is often cited by papers focused on Anomaly Detection Techniques and Applications (2 papers), EEG and Brain-Computer Interfaces (2 papers) and Handwritten Text Recognition Techniques (2 papers). Arnab Kumar Mondal collaborates with scholars based in India, Canada and United States. Arnab Kumar Mondal's co-authors include Prathosh AP, Ajith Abraham, Prabir Kumar Biswas, Shubhashis Sengupta, Swagatam Das, Md Nasir, Vineet Jain, Lalan Kumar, Ayush Tripathi and Sukumar Mishra and has published in prestigious journals such as IEEE Transactions on Smart Grid, Applied Soft Computing and IEEE Transactions on Instrumentation and Measurement.

In The Last Decade

Arnab Kumar Mondal

16 papers receiving 123 citations

Author Peers

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

Author						Papers	Cites
Arnab Kumar Mondal	45	33	25	22	19	19	124
Tamilvizhi Thanarajan	49 1.1×	45 1.4×	28 1.1×	7 0.3×	7 0.4×	16	251
Deng Pan	90 2.0×	30 0.9×	23 0.9×	18 0.8×	53 2.8×	21	237
Igor T. Podolak	60 1.3×	57 1.7×	12 0.5×	30 1.4×	6 0.3×	25	192
A S Remya Ajai	61 1.4×	86 2.6×	17 0.7×	9 0.4×	7 0.4×	21	209
Yan Luo	82 1.8×	64 1.9×	29 1.2×	7 0.3×	5 0.3×	25	179
Chunyan Ji	104 2.3×	27 0.8×	11 0.4×	15 0.7×	5 0.3×	14	255
Mohammad Ali Bagheri	87 1.9×	74 2.2×	9 0.4×	6 0.3×	11 0.6×	19	196
Albert Gu	78 1.7×	39 1.2×	12 0.5×	22 1.0×	7 0.4×	20	168
Antony Browne	125 2.8×	22 0.7×	13 0.5×	27 1.2×	6 0.3×	24	213
Nan Song	177 3.9×	110 3.3×	29 1.2×	12 0.5×	11 0.6×	15	251

Countries citing papers authored by Arnab Kumar Mondal

Since Specialization

Citations

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

Fields of papers citing papers by Arnab Kumar Mondal

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Arnab Kumar Mondal. 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 Arnab Kumar Mondal. The network helps show where Arnab Kumar Mondal may publish in the future.

Co-authorship network of co-authors of Arnab Kumar Mondal

This figure shows the co-authorship network connecting the top 25 collaborators of Arnab Kumar Mondal. A scholar is included among the top collaborators of Arnab Kumar Mondal 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 Arnab Kumar Mondal. Arnab Kumar Mondal 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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