Jason Pelecanos

69 total papers · 1.4k total citations
44 papers, 930 citations indexed

About

Jason Pelecanos is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Jason Pelecanos has authored 44 papers receiving a total of 930 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Artificial Intelligence, 36 papers in Signal Processing and 4 papers in Computer Vision and Pattern Recognition. Recurrent topics in Jason Pelecanos's work include Speech Recognition and Synthesis (42 papers), Speech and Audio Processing (34 papers) and Music and Audio Processing (24 papers). Jason Pelecanos is often cited by papers focused on Speech Recognition and Synthesis (42 papers), Speech and Audio Processing (34 papers) and Music and Audio Processing (24 papers). Jason Pelecanos collaborates with scholars based in United States, Australia and United Kingdom. Jason Pelecanos's co-authors include Sridha Sridharan, Sriram Ganapathy, Seyed Omid Sadjadi, Iain McCowan, Ruhi Sarikaya, Ganesh N. Ramaswamy, D. Nahamoo, Ron Hoory, Hagai Aronowitz and Ignacio López Moreno and has published in prestigious journals such as IEEE Signal Processing Letters, Conference of the International Speech Communication Association and QUT ePrints (Queensland University of Technology).

In The Last Decade

Jason Pelecanos

44 papers receiving 818 citations

Author Peers

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

Author Last Decade Papers Cites
Jason Pelecanos 835 832 57 35 27 44 930
Björn Hoffmeister 488 0.6× 715 0.9× 81 1.4× 45 1.3× 37 1.4× 38 848
J. Wilpon 744 0.9× 796 1.0× 177 3.1× 34 1.0× 45 1.7× 31 962
Wangyou Zhang 683 0.8× 813 1.0× 54 0.9× 61 1.7× 28 1.0× 42 1.0k
Liang Lu 851 1.0× 930 1.1× 72 1.3× 84 2.4× 24 0.9× 64 1.1k
Zhong Meng 679 0.8× 851 1.0× 72 1.3× 37 1.1× 13 0.5× 60 977
Zoltán Tüske 523 0.6× 736 0.9× 83 1.5× 10 0.3× 26 1.0× 47 865
Ehsan Variani 877 1.1× 931 1.1× 82 1.4× 63 1.8× 25 0.9× 22 1.1k
Brecht Desplanques 728 0.9× 803 1.0× 84 1.5× 23 0.7× 48 1.8× 20 988
John Dines 518 0.6× 756 0.9× 66 1.2× 29 0.8× 88 3.3× 58 904
J.-C. Junqua 625 0.7× 609 0.7× 126 2.2× 51 1.5× 74 2.7× 29 796

Countries citing papers authored by Jason Pelecanos

Since Specialization
Citations

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

Fields of papers citing papers by Jason Pelecanos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jason Pelecanos

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