Himadri Mukherjee

123 total papers · 1.2k total citations
49 papers, 639 citations indexed

About

Himadri Mukherjee is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Himadri Mukherjee has authored 49 papers receiving a total of 639 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Artificial Intelligence, 20 papers in Signal Processing and 17 papers in Computer Vision and Pattern Recognition. Recurrent topics in Himadri Mukherjee's work include Music and Audio Processing (17 papers), Speech and Audio Processing (15 papers) and Handwritten Text Recognition Techniques (12 papers). Himadri Mukherjee is often cited by papers focused on Music and Audio Processing (17 papers), Speech and Audio Processing (15 papers) and Handwritten Text Recognition Techniques (12 papers). Himadri Mukherjee collaborates with scholars based in India, United States and United Arab Emirates. Himadri Mukherjee's co-authors include Kaushik Roy, Sk Md Obaidullah, KC Santosh, Ankita Dhar, Subhankar Ghosh, Santanu Phadikar, Mridul Ghosh, Nibaran Das, Arkaprabha Sau and Hanan Salam and has published in prestigious journals such as IEEE Access, Neural Computing and Applications and Artificial Intelligence Review.

In The Last Decade

Himadri Mukherjee

45 papers receiving 617 citations

Author Peers

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

Author Last Decade Papers Cites
Himadri Mukherjee 316 202 136 132 76 49 639
Sidra Abbas 290 0.9× 75 0.4× 82 0.6× 97 0.7× 23 0.3× 29 689
Vajira Thambawita 242 0.8× 181 0.9× 26 0.2× 132 1.0× 56 0.7× 33 765
María Teresa Garcí­a-Ordás 196 0.6× 57 0.3× 67 0.5× 62 0.5× 66 0.9× 46 705
Arslan Shaukat 133 0.4× 203 1.0× 69 0.5× 149 1.1× 66 0.9× 64 698
Norliza Mohd Noor 142 0.4× 244 1.2× 20 0.1× 171 1.3× 111 1.5× 116 638
Abdullah Y. Muaad 276 0.9× 170 0.8× 15 0.1× 99 0.8× 46 0.6× 37 696
Samaneh Kouchaki 120 0.4× 72 0.4× 108 0.8× 39 0.3× 25 0.3× 54 728
Carmen Benavides 186 0.6× 39 0.2× 123 0.9× 29 0.2× 63 0.8× 43 635
Talha Burak Alakuş 319 1.0× 375 1.9× 38 0.3× 92 0.7× 39 0.5× 26 784
Hongyu Wang 249 0.8× 231 1.1× 21 0.2× 173 1.3× 37 0.5× 69 759

Countries citing papers authored by Himadri Mukherjee

Since Specialization
Citations

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

Fields of papers citing papers by Himadri Mukherjee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Himadri Mukherjee

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