Gabriel Perdue

3.5k citations
30 papers · 290 · h-index 10

Impact in

Papers in

    • Quantum Computing Algorithms and Architecture 9
    • Quantum Information and Cryptography 6
    • Neural Networks and Reservoir Computing 4
    • Particle physics theoretical and experimental studies 8
    • Neutrino Physics Research 5
    • Particle Detector Development and Performance 3
    • Astrophysics and Cosmic Phenomena 3

Gabriel Perdue

24 papers receiving 278 citations

Peers

Gabriel Perdue
Comparison fields: 5 of 51
  • Nuclear and High Energy Physics 65
  • Artificial Intelligence 154
  • Instrumentation 13
  • Computational Mathematics 2
  • Atomic and Molecular Physics, and Optics 92
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Gabriel Perdue relative to Gustavo Cancelo United States Gustavo Cancelo's profile →
Citations per field
00.5×1.5×1.9×
Gustavo Cancelo · 1×
Citations per year

Countries citing papers authored by Gabriel Perdue

Since Specialization
Citations

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

Fields of papers citing papers by Gabriel Perdue

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202064
2 202131
3 201730
4 202028
5 202122
6 202420
7 202214
8 202314
9 202310
10 201710
11 20238
12 20176
13 20216
14 20216
15 20225
16 20195
17 20252
18 20232
19 20231
20 20231

About Gabriel Perdue

Gabriel Perdue is a scholar working on Artificial Intelligence, Nuclear and High Energy Physics, Atomic and Molecular Physics, and Optics, Electrical and Electronic Engineering and Astronomy and Astrophysics, having authored 30 papers that have together received 290 indexed citations. Recurring topics across this work include Quantum Computing Algorithms and Architecture (9 papers), Particle physics theoretical and experimental studies (8 papers), Quantum Information and Cryptography (6 papers), Neutrino Physics Research (5 papers), Neural Networks and Reservoir Computing (4 papers), Particle Detector Development and Performance (3 papers), Astrophysics and Cosmic Phenomena (3 papers) and Scientific Computing and Data Management (3 papers). The work is most often cited by research in Nuclear and High Energy Physics (65 citations), Artificial Intelligence (154 citations), Instrumentation (13 citations), Computational Mathematics (2 citations) and Atomic and Molecular Physics, and Optics (92 citations). Gabriel Perdue has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include Andy C. Y. Li, Alessandro Roggero, Rajan Gupta, J. Carlson, Steven R. Young, Travis Johnston, B. Nord, Robert M. Patton, Sandeep Madireddy and Gregory F. Snyder. Their work appears in journals such as Machine Learning Science and Technology, Quantum Machine Intelligence, Physical review. A, Quantum Science and Technology and Physical review. D.

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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