Steven Sandoval

33 papers receiving 254 citations

Peers

Steven Sandoval
Comparison fields: 5 of 67
  • Signal Processing 73
  • Experimental and Cognitive Psychology 74
  • Artificial Intelligence 92
  • Physiology 66
  • Speech and Hearing 16
Replace Jacqueline Walker with:
Jacqueline Walker Ireland
Andrew Lundberg United States
Sean A. Fulop United States
Sergey Pugachevskiy Germany
P. Vijayalakshmi India
Julien Pinquier France
Tokihiko Kaburagi Japan
Daniel Aalto Canada
Rajeev Rajan India
Agustín Álvarez-Marquina Spain
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Citations per field
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Jacqueline Walker · 1×
Citations per year

Countries citing papers authored by Steven Sandoval

Since Specialization
Citations

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

Fields of papers citing papers by Steven Sandoval

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201362
2 201121
3 201419
4 202017
5 202315
6 201414
7 201813
8 201312
9 201810
10 20178
11 20068
12 20227
13 20187
14 20206
15 20204
16 20204
17 20214
18 20114
19 20243
20 20133

About Steven Sandoval

Steven Sandoval is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering and Aerospace Engineering, having authored 39 papers that have together received 261 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (10 papers), Speech and Audio Processing (9 papers), Phonetics and Phonology Research (6 papers), Image and Signal Denoising Methods (6 papers), Machine Fault Diagnosis Techniques (6 papers), Voice and Speech Disorders (5 papers), Space Exploration and Technology (4 papers) and Advanced Image Fusion Techniques (4 papers). The work is most often cited by research in Signal Processing (73 citations), Experimental and Cognitive Psychology (74 citations), Artificial Intelligence (92 citations), Physiology (66 citations) and Speech and Hearing (16 citations). Steven Sandoval has collaborated with scholars based in United States, Netherlands and Sweden. Frequent co-authors include Phillip L. De León, Julie Liss, Rene L. Utianski, Visar Berisha, Andreas Spanias, Laura E. Boucheron, David Voelz, Adrian Stoica, Thomas T. Liu and Sukanta Basu. Their work appears in journals such as The Journal of the Acoustical Society of America, Applied Optics, Optics Express, Frontiers in Psychology and American Journal of Speech-Language Pathology.

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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