Vikramjit Mitra

2.0k citations
88 papers · 1.5k · h-index 24

Impact in

Papers in

Vikramjit Mitra

86 papers receiving 1.3k citations

Peers

Vikramjit Mitra
Comparison fields: 5 of 132
  • Signal Processing 836
  • Experimental and Cognitive Psychology 396
  • Artificial Intelligence 991
  • Computer Vision and Pattern Recognition 146
  • Developmental Biology 9
Replace Mustaqeem Mustaqeem with:
Mustaqeem Mustaqeem South Korea
Jun Deng Germany
Soonil Kwon South Korea
Panagiotis Tzirakis United Kingdom
Ziping Zhao China
Lijiang Chen China
Koichi Shinoda Japan
Tin Lay Nwe Singapore
Haytham M. Fayek Australia
Jouni Pohjalainen Finland
Vikramjit Mitra relative to Mustaqeem Mustaqeem South Korea Mustaqeem Mustaqeem's profile →
Citations per field
00.5×1.5×2.0×
Mustaqeem Mustaqeem · 1×
Citations per year

Countries citing papers authored by Vikramjit Mitra

Since Specialization
Citations

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

Fields of papers citing papers by Vikramjit Mitra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 88 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006121
2 201279
3 200668
4 201756
5 201252
6 201151
7 201451
8 201348
9 201042
10 201340
11 201435
12 201534
13 201433
14 201732
15 201432
16 201332
17 201931
18 201529
19 201428
20 201727

About Vikramjit Mitra

Vikramjit Mitra is a scholar working on Artificial Intelligence, Signal Processing, Experimental and Cognitive Psychology, Computer Vision and Pattern Recognition and Social Psychology, having authored 88 papers that have together received 1.5k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (64 papers), Speech and Audio Processing (59 papers), Music and Audio Processing (42 papers), Phonetics and Phonology Research (21 papers), Emotion and Mood Recognition (8 papers), Music Technology and Sound Studies (4 papers), Mental Health via Writing (3 papers) and Natural Language Processing Techniques (3 papers). The work is most often cited by research in Signal Processing (836 citations), Experimental and Cognitive Psychology (396 citations), Artificial Intelligence (991 citations), Computer Vision and Pattern Recognition (146 citations) and Developmental Biology (9 citations). Vikramjit Mitra has collaborated with scholars based in United States, South Korea and Argentina. Frequent co-authors include Carol Espy-Wilson, Horacio Franco, Chia-Jiu Wang, Martin Graciarena, Hosung Nam, Satarupa Banerjee, Elliot Saltzman, Louis Goldstein, Ganesh Sivaraman and Jane Metcalf. Their work appears in journals such as The Journal of the Acoustical Society of America, Speech Communication, IEEE Journal of Selected Topics in Signal Processing, Computer Speech & Language and Scientific Reports.

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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