Dimitri Kanevsky

1.6k total citations
59 papers, 1.0k citations indexed

About

Dimitri Kanevsky is a scholar working on Artificial Intelligence, Signal Processing and Computational Mechanics. According to data from OpenAlex, Dimitri Kanevsky has authored 59 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Artificial Intelligence, 32 papers in Signal Processing and 10 papers in Computational Mechanics. Recurrent topics in Dimitri Kanevsky's work include Speech and Audio Processing (26 papers), Speech Recognition and Synthesis (25 papers) and Music and Audio Processing (15 papers). Dimitri Kanevsky is often cited by papers focused on Speech and Audio Processing (26 papers), Speech Recognition and Synthesis (25 papers) and Music and Audio Processing (15 papers). Dimitri Kanevsky collaborates with scholars based in United States, United Kingdom and Israel. Dimitri Kanevsky's co-authors include Bhuvana Ramabhadran, D. Nahamoo, Tara N. Sainath, Avishy Carmi, Arthur Nádas, P.S. Gopalakrishnan, Daniel Povey, Brian Kingsbury, Karthik Visweswariah and George Saon and has published in prestigious journals such as IEEE Transactions on Information Theory, Communications of the ACM and IEEE Transactions on Signal Processing.

In The Last Decade

Dimitri Kanevsky

55 papers receiving 926 citations

Peers

Dimitri Kanevsky
Comparison fields: 5 of 79
  • Artificial Intelligence 757
  • Signal Processing 611
  • Computer Vision and Pattern Recognition 139
  • Computational Mechanics 136
  • Computer Networks and Communications 60
Replace Michiel Bacchiani with:
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Citations per field, relative to Dimitri Kanevsky
Dimitri Kanevsky · 1×
Citations per year, relative to Dimitri Kanevsky
Dimitri Kanevsky · 1×

Countries citing papers authored by Dimitri Kanevsky

Since Specialization
Citations

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

Fields of papers citing papers by Dimitri Kanevsky

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Dimitri Kanevsky

This figure shows the co-authorship network connecting the top 25 collaborators of Dimitri Kanevsky. A scholar is included among the top collaborators of Dimitri Kanevsky 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 Dimitri Kanevsky. Dimitri Kanevsky is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 4
2 0
3 17
4
Self-managed Speech Therapy
1
5 13
6 0
7
Exemplar-based processing for speech recognition
6
8 3
9 42
10 6
11 1
12 250
13 3
14 3
15 5
16 35
17 21
18 2
19 16
20 3

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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