Leonard J. Trejo

56 total papers · 2.6k total citations
31 papers, 1.9k citations indexed

About

Leonard J. Trejo is a scholar working on Cognitive Neuroscience, Signal Processing and Cellular and Molecular Neuroscience. According to data from OpenAlex, Leonard J. Trejo has authored 31 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Cognitive Neuroscience, 9 papers in Signal Processing and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Leonard J. Trejo's work include EEG and Brain-Computer Interfaces (12 papers), Blind Source Separation Techniques (8 papers) and Spectroscopy and Chemometric Analyses (4 papers). Leonard J. Trejo is often cited by papers focused on EEG and Brain-Computer Interfaces (12 papers), Blind Source Separation Techniques (8 papers) and Spectroscopy and Chemometric Analyses (4 papers). Leonard J. Trejo collaborates with scholars based in United States, Austria and Slovakia. Leonard J. Trejo's co-authors include Roman Rosipal, Bryan Matthews, Carol M. Cicerone, Arthur F. Kramer, Andrzej Cichocki, Mark Girolami, Leslie D. Montgomery, Karla A. Kubitz, M. Shensa and Kevin Wheeler and has published in prestigious journals such as Brain Research, Vision Research and Psychophysiology.

In The Last Decade

Leonard J. Trejo

28 papers receiving 1.8k citations

Hit Papers

Kernel partial least squa... 2002 2026 2010 2018 2002 200 400 600

Author Peers

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

Author Last Decade Papers Cites
Leonard J. Trejo 732 344 328 300 252 31 1.9k
Roman Rosipal 489 0.7× 404 1.2× 385 1.2× 175 0.6× 296 1.2× 37 1.7k
Hualou Liang 2.0k 2.8× 194 0.6× 84 0.3× 361 1.2× 356 1.4× 90 3.2k
Hamed Azami 696 1.0× 866 2.5× 70 0.2× 69 0.2× 362 1.4× 60 2.5k
Hong-Bo Xie 796 1.1× 299 0.9× 32 0.1× 137 0.5× 243 1.0× 47 2.1k
Michael Eichler 608 0.8× 306 0.9× 62 0.2× 103 0.3× 251 1.0× 51 1.7k
Jordi Solé‐Casals 842 1.2× 217 0.6× 51 0.2× 187 0.6× 283 1.1× 127 1.9k
James V. Stone 842 1.2× 65 0.2× 153 0.5× 85 0.3× 216 0.9× 44 1.7k
Johan Himberg 1.4k 1.8× 109 0.3× 85 0.3× 73 0.2× 580 2.3× 24 3.1k
Liang Zou 535 0.7× 81 0.2× 129 0.4× 311 1.0× 379 1.5× 123 2.8k
Daniel Rivero 975 1.3× 81 0.2× 97 0.3× 188 0.6× 458 1.8× 65 2.1k

Countries citing papers authored by Leonard J. Trejo

Since Specialization
Citations

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

Fields of papers citing papers by Leonard J. Trejo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Leonard J. Trejo. 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 Leonard J. Trejo. The network helps show where Leonard J. Trejo may publish in the future.

Co-authorship network of co-authors of Leonard J. Trejo

This figure shows the co-authorship network connecting the top 25 collaborators of Leonard J. Trejo. A scholar is included among the top collaborators of Leonard J. Trejo 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 Leonard J. Trejo. Leonard J. Trejo 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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